Search Results for author: Qian Wang

Found 152 papers, 52 papers with code

Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering

no code implementations COLING 2022 Qian Wang, Jiajun Zhang

However, the existing clustering methods based on language similarity cannot handle the asymmetric problem in multilingual NMT, i. e., one translation task A can benefit from another translation task B but task B will be harmed by task A.

Clustering Machine Translation +3

Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening

no code implementations22 Feb 2024 Zhenrong Shen, Manman Fei, Xin Wang, Jiangdong Cai, Sheng Wang, Lichi Zhang, Qian Wang

In the first Global Image Generation stage, a Normal Image Generator is designed to generate cytopathological images full of normal cervical cells.

Cell Detection Data Augmentation +1

Ensure Timeliness and Accuracy: A Novel Sliding Window Data Stream Paradigm for Live Streaming Recommendation

no code implementations22 Feb 2024 Fengqi Liang, Baigong Zheng, Liqin Zhao, Guorui Zhou, Qian Wang, Yanan Niu

In this paper, we propose a new data stream design paradigm, dubbed Sliver, that addresses the timeliness and accuracy problem of labels by reducing the window size and implementing a sliding window correspondingly.

Recommendation Systems

BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes

no code implementations20 Feb 2024 Qian Wang, Zemin Liu, Zhen Zhang, Bingsheng He

Class imbalance in graph-structured data, where minor classes are significantly underrepresented, poses a critical challenge for Graph Neural Networks (GNNs).

Classification Node Classification

360DVD: Controllable Panorama Video Generation with 360-Degree Video Diffusion Model

no code implementations12 Jan 2024 Qian Wang, Weiqi Li, Chong Mou, Xinhua Cheng, Jian Zhang

Recently, the emerging text-to-video (T2V) diffusion methods demonstrate notable effectiveness in standard video generation.

Video Generation

Every Node is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering

1 code implementation12 Jan 2024 Pengfei Zhu, Qian Wang, Yu Wang, Jialu Li, QinGhua Hu

In this paper, we propose to dynamically learn the weights of SSL tasks for different nodes and fuse the embeddings learned from different SSL tasks to boost performance.

Clustering Graph Clustering +1

Enhancing the Performance of DeepReach on High-Dimensional Systems through Optimizing Activation Functions

no code implementations29 Dec 2023 Qian Wang, Tianhao Wu

Hamilton-Jacobi Reachability Analysis is a formal verification method that guarantees performance and safety for dynamical systems and is widely applicable to various tasks and challenges.

Continual Adversarial Defense

no code implementations15 Dec 2023 Qian Wang, Yaoyao Liu, Hefei Ling, Yingwei Li, Qihao Liu, Ping Li, Jiazhong Chen, Alan Yuille, Ning Yu

In response to the rapidly evolving nature of adversarial attacks on a monthly basis, numerous defenses have been proposed to generalize against as many known attacks as possible.

Adversarial Defense Continual Learning +2

CLIP in Medical Imaging: A Comprehensive Survey

1 code implementation12 Dec 2023 Zihao Zhao, Yuxiao Liu, Han Wu, Yonghao Li, Sheng Wang, Lin Teng, Disheng Liu, Zhiming Cui, Qian Wang, Dinggang Shen

With the aim of facilitating a deeper understanding of this promising direction, this survey offers an in-depth exploration of the CLIP paradigm within the domain of medical imaging, regarding both refined CLIP pre-training and CLIP-driven applications.

Mining Gaze for Contrastive Learning toward Computer-Assisted Diagnosis

1 code implementation11 Dec 2023 Zihao Zhao, Sheng Wang, Qian Wang, Dinggang Shen

Accordingly, we introduce the Medical contrastive Gaze Image Pre-training (McGIP) as a plug-and-play module for contrastive learning frameworks.

Contrastive Learning Semantic Similarity +1

MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosis

1 code implementation14 Nov 2023 Yitao Zhu, Zhenrong Shen, Zihao Zhao, Sheng Wang, Xin Wang, Xiangyu Zhao, Dinggang Shen, Qian Wang

By fixing the weight of ViT models and only adding small low-rank plug-ins, we achieve competitive results on various diagnosis tasks across different imaging modalities using only a few trainable parameters.

ETGraph: A Pioneering Dataset Bridging Ethereum and Twitter

no code implementations2 Oct 2023 Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He

While numerous public blockchain datasets are available, their utility is constrained by a singular focus on blockchain data.

Link Prediction

Large Language Model Soft Ideologization via AI-Self-Consciousness

no code implementations28 Sep 2023 Xiaotian Zhou, Qian Wang, XiaoFeng Wang, Haixu Tang, Xiaozhong Liu

Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks.

Language Modelling Large Language Model

Mapping EEG Signals to Visual Stimuli: A Deep Learning Approach to Match vs. Mismatch Classification

no code implementations8 Sep 2023 Yiqian Yang, Zhengqiao Zhao, Qian Wang, Yan Yang, Jingdong Chen

Existing approaches to modeling associations between visual stimuli and brain responses are facing difficulties in handling between-subject variance and model generalization.

EEG Video Reconstruction

Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening

2 code implementations6 Sep 2023 Jiangdong Cai, Honglin Xiong, Maosong Cao, Luyan Liu, Lichi Zhang, Qian Wang

Finally, we use a contrastive learning method to alleviate the overfitting caused by the style gap of WSIs and suppress the attention to false positive regions.

Classification Contrastive Learning

AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation

1 code implementation2 Sep 2023 Xiangyu Zhao, Sheng Wang, Zhiyun Song, Zhenrong Shen, Linlin Yao, Haolei Yuan, Qian Wang, Lichi Zhang

To address these issues, we propose a novel one-shot medical image segmentation method with adversarial training and label error rectification (AdLER), with the aim of improving the diversity of generated data and correcting label errors to enhance segmentation performance.

Anatomy Data Augmentation +4

A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions

1 code implementation26 Aug 2023 Zemin Liu, Yuan Li, Nan Chen, Qian Wang, Bryan Hooi, Bingsheng He

However, these methods often suffer from data imbalance, a common issue in graph data where certain segments possess abundant data while others are scarce, thereby leading to biased learning outcomes.

Graph Learning Link Prediction +1

Recap: Detecting Deepfake Video with Unpredictable Tampered Traces via Recovering Faces and Mapping Recovered Faces

no code implementations19 Aug 2023 Juan Hu, Xin Liao, Difei Gao, Satoshi Tsutsui, Qian Wang, Zheng Qin, Mike Zheng Shou

In the recovering stage, the model focuses on randomly masking regions of interest (ROIs) and reconstructing real faces without unpredictable tampered traces, resulting in a relatively good recovery effect for real faces while a poor recovery effect for fake faces.

DeepFake Detection Face Swapping

Downstream-agnostic Adversarial Examples

1 code implementation ICCV 2023 Ziqi Zhou, Shengshan Hu, Ruizhi Zhao, Qian Wang, Leo Yu Zhang, Junhui Hou, Hai Jin

AdvEncoder aims to construct a universal adversarial perturbation or patch for a set of natural images that can fool all the downstream tasks inheriting the victim pre-trained encoder.

Self-Supervised Learning

CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification

1 code implementation12 Jul 2023 Zhenrong Shen, Maosong Cao, Sheng Wang, Lichi Zhang, Qian Wang

In this paper, we propose CellGAN to synthesize cytopathological images of various cervical cell types for augmenting patch-level cell classification.

Image Classification Image Generation +1

Multi-Scenario Ranking with Adaptive Feature Learning

no code implementations29 Jun 2023 Yu Tian, Bofang Li, Si Chen, Xubin Li, Hongbo Deng, Jian Xu, Bo Zheng, Qian Wang, Chenliang Li

Recently, Multi-Scenario Learning (MSL) is widely used in recommendation and retrieval systems in the industry because it facilitates transfer learning from different scenarios, mitigating data sparsity and reducing maintenance cost.

Retrieval Transfer Learning

Paradigm Shift in Sustainability Disclosure Analysis: Empowering Stakeholders with CHATREPORT, a Language Model-Based Tool

no code implementations27 Jun 2023 Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni, Mathias Kraus, Glen Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Ashraf Vaghefi, Qian Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu, Markus Leippold

This paper introduces a novel approach to enhance Large Language Models (LLMs) with expert knowledge to automate the analysis of corporate sustainability reports by benchmarking them against the Task Force for Climate-Related Financial Disclosures (TCFD) recommendations.

Benchmarking Language Modelling

Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets

no code implementations13 Jun 2023 Yurong Chen, Qian Wang, Zhijian Duan, Haoran Sun, Zhaohua Chen, Xiang Yan, Xiaotie Deng

To the best of our knowledge, we are the first to consider bidder coordination in online repeated auctions with constraints.

Semantic Segmentation on VSPW Dataset through Contrastive Loss and Multi-dataset Training Approach

no code implementations6 Jun 2023 Min Yan, Qianxiong Ning, Qian Wang

Video scene parsing incorporates temporal information, which can enhance the consistency and accuracy of predictions compared to image scene parsing.

Scene Parsing Semantic Segmentation +1

Deep Joint Source-Channel Coding for Wireless Image Transmission with Entropy-Aware Adaptive Rate Control

no code implementations5 Jun 2023 Weixuan Chen, Yuhao Chen, Qianqian Yang, Chongwen Huang, Qian Wang, Zhaoyang Zhang

Adaptive rate control for deep joint source and channel coding (JSCC) is considered as an effective approach to transmit sufficient information in scenarios with limited communication resources.

ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs

1 code implementation25 May 2023 Zihao Zhao, Sheng Wang, Jinchen Gu, Yitao Zhu, Lanzhuju Mei, Zixu Zhuang, Zhiming Cui, Qian Wang, Dinggang Shen

However, current works in this field are plagued by limitations, specifically a restricted scope of applicable image domains and the provision of unreliable medical advice.


GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentation

no code implementations24 May 2023 Wei Zhou, Qian Wang, Weiwei Jin, Xinzhe Shi, Ying He

Local Transformer uses a dynamic graph to calculate all neighboring point weights by intra-domain cross-attention with dynamically updated graph relations, so that every neighboring point could affect the features of centroid with different weights; Global Transformer enlarges the receptive field of Local Transformer by a global self-attention.

3D Point Cloud Classification Point Cloud Classification +1

When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP

2 code implementations23 May 2023 Jingwei Ni, Zhijing Jin, Qian Wang, Mrinmaya Sachan, Markus Leippold

Due to the task difficulty and data scarcity in the Financial NLP domain, we explore when aggregating such diverse skills from multiple datasets with MTL can work.

Multi-Task Learning Open-Ended Question Answering +1

Machine learning enhanced real-time aerodynamic forces prediction based on sparse pressure sensor inputs

no code implementations16 May 2023 Junming Duan, Qian Wang, Jan S. Hesthaven

The model is built on a linear term that can make a reasonably accurate prediction and a nonlinear correction for accuracy improvement.

Autonomous Navigation

Learning Better Contrastive View from Radiologist's Gaze

1 code implementation15 May 2023 Sheng Wang, Zixu Zhuang, Xi Ouyang, Lichi Zhang, Zheren Li, Chong Ma, Tianming Liu, Dinggang Shen, Qian Wang

Then, we propose a novel augmentation method, i. e., FocusContrast, to learn from radiologists' gaze in diagnosis and generate contrastive views for medical images with guidance from radiologists' visual attention.

Contrastive Learning Data Augmentation

Backdoor Attack with Sparse and Invisible Trigger

1 code implementation11 May 2023 Yinghua Gao, Yiming Li, Xueluan Gong, Zhifeng Li, Shu-Tao Xia, Qian Wang

More importantly, it is not feasible to simply combine existing methods to design an effective sparse and invisible backdoor attack.

Backdoor Attack

VTPNet for 3D deep learning on point cloud

no code implementations10 May 2023 Wei Zhou, Weiwei Jin, Qian Wang, Yifan Wang, Dekui Wang, Xingxing Hao, Yongxiang Yu

Recently, Transformer-based methods for point cloud learning have achieved good results on various point cloud learning benchmarks.

Semantic Segmentation

Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction

no code implementations4 May 2023 Qi Wang, Zhijie Wen, Jun Shi, Qian Wang, Dinggang Shen, Shihui Ying

Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive disease diagnosis in clinical medicine.

MRI Reconstruction

Detecting Adversarial Faces Using Only Real Face Self-Perturbations

1 code implementation22 Apr 2023 Qian Wang, Yongqin Xian, Hefei Ling, Jinyuan Zhang, Xiaorui Lin, Ping Li, Jiazhong Chen, Ning Yu

Adversarial attacks aim to disturb the functionality of a target system by adding specific noise to the input samples, bringing potential threats to security and robustness when applied to facial recognition systems.

Face Detection

Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion

no code implementations16 Apr 2023 Xin Wang, Zhenrong Shen, Zhiyun Song, Sheng Wang, Mengjun Liu, Lichi Zhang, Kai Xuan, Qian Wang

Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resolution.


chatClimate: Grounding Conversational AI in Climate Science

no code implementations11 Apr 2023 Saeid Ashraf Vaghefi, Qian Wang, Veruska Muccione, Jingwei Ni, Mathias Kraus, Julia Bingler, Tobias Schimanski, Chiara Colesanti-Senni, Nicolas Webersinke, Christrian Huggel, Markus Leippold

The answers and their sources were evaluated by our team of IPCC authors, who used their expert knowledge to score the accuracy of the answers from 1 (very-low) to 5 (very-high).

Hallucination Question Answering

DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task

1 code implementation3 Apr 2023 Honglin Xiong, Sheng Wang, Yitao Zhu, Zihao Zhao, Yuxiao Liu, Linlin Huang, Qian Wang, Dinggang Shen

The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable.

Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data

no code implementations31 Mar 2023 Qian Wang, Kamran Paynabar

Point cloud data are widely used in manufacturing applications for process inspection, modeling, monitoring and optimization.

Dimensionality Reduction regression

Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection

no code implementations3 Mar 2023 Juan Hu, Xin Liao, Difei Gao, Satoshi Tsutsui, Qian Wang, Zheng Qin, Mike Zheng Shou

Specifically, given a real face image, we first pretrain a masked autoencoder to learn facial part consistency by dividing faces into three parts and randomly masking ROIs, which are then recovered based on the unmasked facial parts.

DeepFake Detection Face Swapping

ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models

1 code implementation14 Feb 2023 Sheng Wang, Zihao Zhao, Xi Ouyang, Qian Wang, Dinggang Shen

Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice.

Decision Making Lesion Segmentation +1

RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation

1 code implementation13 Jan 2023 Xiangyu Zhao, Zengxin Qi, Sheng Wang, Qian Wang, Xuehai Wu, Ying Mao, Lichi Zhang

However, learning a robust representation from numerous unlabeled images remains challenging due to potential noise in pseudo labels and insufficient class separability in feature space, which undermines the performance of current semi-supervised segmentation approaches.

Contrastive Learning Image Segmentation +3

Panoptic Compositional Feature Field for Editable Scene Rendering With Network-Inferred Labels via Metric Learning

no code implementations CVPR 2023 Xinhua Cheng, Yanmin Wu, Mengxi Jia, Qian Wang, Jian Zhang

In this work, we attempt to learn an object-compositional neural implicit representation for editable scene rendering by leveraging labels inferred from the off-the-shelf 2D panoptic segmentation networks instead of the ground truth annotations.

Metric Learning Novel View Synthesis +1

Implicit Identity Driven Deepfake Face Swapping Detection

no code implementations CVPR 2023 Baojin Huang, Zhongyuan Wang, Jifan Yang, Jiaxin Ai, Qin Zou, Qian Wang, Dengpan Ye

Face swapping aims to replace the target face with the source face and generate the fake face that the human cannot distinguish between real and fake.

Face Swapping

Integrating multi-type aberrations from DNA and RNA through dynamic mapping gene space for subtype-specific breast cancer driver discovery

no code implementations9 Dec 2022 Jianing Xi, Zhen Deng, Yang Liu, Qian Wang, Wen Shi

Notably, cancer driver events would occur due to not only DNA aberrations but also RNA alternations, but integrating multi-type aberrations from both DNA and RNA is still a challenging task for breast cancer drivers.

Specificity Vocal Bursts Type Prediction

On Fine-Tuned Deep Features for Unsupervised Domain Adaptation

no code implementations25 Oct 2022 Qian Wang, Toby P. Breckon

Prior feature transformation based approaches to Unsupervised Domain Adaptation (UDA) employ the deep features extracted by pre-trained deep models without fine-tuning them on the specific source or target domain data for a particular domain adaptation task.

Unsupervised Domain Adaptation

Whole Page Unbiased Learning to Rank

no code implementations19 Oct 2022 Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin

To address the above challenges, we propose a Bias Agnostic whole-page unbiased Learning to rank algorithm, named BAL, to automatically find the user behavior model with causal discovery and mitigate the biases induced by multiple SERP features with no specific design.

Causal Discovery Information Retrieval +2

Probabilistic Generative Transformer Language models for Generative Design of Molecules

1 code implementation20 Sep 2022 Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu

Self-supervised neural language models have recently found wide applications in generative design of organic molecules and protein sequences as well as representation learning for downstream structure classification and functional prediction.

Language Modelling Representation Learning

Image Synthesis with Disentangled Attributes for Chest X-Ray Nodule Augmentation and Detection

no code implementations19 Jul 2022 Zhenrong Shen, Xi Ouyang, Bin Xiao, Jie-Zhi Cheng, Qian Wang, Dinggang Shen

Moreover, we propose to synthesize nodule CXR images by controlling the disentangled nodule attributes for data augmentation, in order to better compensate for the nodules that are easily missed in the detection task.

Attribute Data Augmentation +2

Dynamic Budget Throttling in Repeated Second-Price Auctions

no code implementations11 Jul 2022 Zhaohua Chen, Chang Wang, Qian Wang, Yuqi Pan, Zhuming Shi, Zheng Cai, Yukun Ren, Zhihua Zhu, Xiaotie Deng

Among various budget control methods, throttling has emerged as a popular choice, managing an advertiser's total expenditure by selecting only a subset of auctions to participate in.

DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring

no code implementations30 Jun 2022 Shuang Dai, Fanlin Meng, Qian Wang, Xizhong Chen

Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumption, can help analyze electricity consumption behaviours of users and enable practical smart energy and smart grid applications.

Federated Learning Non-Intrusive Load Monitoring +1

Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning

no code implementations25 May 2022 Chong Ma, Lin Zhao, Yuzhong Chen, Lu Zhang, Zhenxiang Xiao, Haixing Dai, David Liu, Zihao Wu, Zhengliang Liu, Sheng Wang, Jiaxing Gao, Changhe Li, Xi Jiang, Tuo Zhang, Qian Wang, Dinggang Shen, Dajiang Zhu, Tianming Liu

To address this problem, we propose to infuse human experts' intelligence and domain knowledge into the training of deep neural networks.

Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing

no code implementations23 May 2022 Xin Wang, Sheng Wang, Honglin Xiong, Kai Xuan, Zixu Zhuang, Mengjun Liu, Zhenrong Shen, Xiangyu Zhao, Lichi Zhang, Qian Wang

Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resolution.

Computational Efficiency Super-Resolution

Deep Generalized Unfolding Networks for Image Restoration

1 code implementation CVPR 2022 Chong Mou, Qian Wang, Jian Zhang

Concretely, without loss of interpretability, we integrate a gradient estimation strategy into the gradient descent step of the Proximal Gradient Descent (PGD) algorithm, driving it to deal with complex and real-world image degradation.

Image Restoration

Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis

1 code implementation6 Apr 2022 Sheng Wang, Xi Ouyang, Tianming Liu, Qian Wang, Dinggang Shen

In this paper, we demonstrate that the eye movement of radiologists reading medical images can be a new form of supervision to train the DNN-based computer-aided diagnosis (CAD) system.

FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons

1 code implementation6 Apr 2022 Xuanqi Gao, Juan Zhai, Shiqing Ma, Chao Shen, Yufei Chen, Qian Wang

To solve this issue, there has been a number of work trying to improve model fairness by using an adversarial game in model level.


Automatic Facial Skin Feature Detection for Everyone

no code implementations30 Mar 2022 Qian Zheng, Ankur Purwar, Heng Zhao, Guang Liang Lim, Ling Li, Debasish Behera, Qian Wang, Min Tan, Rizhao Cai, Jennifer Werner, Dennis Sng, Maurice van Steensel, Weisi Lin, Alex C Kot

We present an automatic facial skin feature detection method that works across a variety of skin tones and age groups for selfies in the wild.

Product Recommendation

Towards Benchmarking and Evaluating Deepfake Detection

no code implementations4 Mar 2022 Chenhao Lin, Jingyi Deng, Pengbin Hu, Chao Shen, Qian Wang, Qi Li

Deepfake detection automatically recognizes the manipulated medias through the analysis of the difference between manipulated and non-altered videos.

Benchmarking DeepFake Detection +1

Transformers in Medical Image Analysis: A Review

no code implementations24 Feb 2022 Kelei He, Chen Gan, Zhuoyuan Li, Islem Rekik, Zihao Yin, Wen Ji, Yang Gao, Qian Wang, Junfeng Zhang, Dinggang Shen

Transformers have dominated the field of natural language processing, and recently impacted the computer vision area.

Image Generation

Parameter Differentiation based Multilingual Neural Machine Translation

2 code implementations27 Dec 2021 Qian Wang, Jiajun Zhang

Further analyses reveal that the parameter sharing configuration obtained by our method correlates well with the linguistic proximities.

Machine Translation Open-Ended Question Answering +2

Learning Hierarchical Attention for Weakly-supervised Chest X-Ray Abnormality Localization and Diagnosis

1 code implementation23 Dec 2021 Xi Ouyang, Srikrishna Karanam, Ziyan Wu, Terrence Chen, Jiayu Huo, Xiang Sean Zhou, Qian Wang, Jie-Zhi Cheng

However, doing this accurately will require a large amount of disease localization annotations by clinical experts, a task that is prohibitively expensive to accomplish for most applications.

Decision Making

Reconstructing Training Data from Diverse ML Models by Ensemble Inversion

no code implementations5 Nov 2021 Qian Wang, Daniel Kurz

This technique leads to noticeable improvements of the quality of the generated samples with distinguishable features of the dataset entities compared to MI of a single ML model.

Generative Adversarial Network

Progressively Select and Reject Pseudo-labelled Samples for Open-Set Domain Adaptation

no code implementations25 Oct 2021 Qian Wang, Fanlin Meng, Toby P. Breckon

The common subspace learning algorithm OSLPP simultaneously aligns the labelled source data and pseudo-labelled target data from known classes and pushes the rejected target data away from the known classes.

Domain Adaptation Image Classification +1

Anti-Distillation Backdoor Attacks: Backdoors Can Really Survive in Knowledge Distillation

1 code implementation MM - Proceedings of the ACM International Conference on Multimedia 2021 Yunjie Ge, Qian Wang, Baolin Zheng, Xinlu Zhuang, Qi Li, Chao Shen, Cong Wang

In this paper, we, for the first time, propose a novel Anti-Distillation Backdoor Attack (ADBA), in which the backdoor embedded in the public teacher model can survive the knowledge distillation process and thus be transferred to secret distilled student models.

Backdoor Attack Knowledge Distillation

Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information

no code implementations19 Oct 2021 Baolin Zheng, Peipei Jiang, Qian Wang, Qi Li, Chao Shen, Cong Wang, Yunjie Ge, Qingyang Teng, Shenyi Zhang

For commercial cloud speech APIs, we propose Occam, a decision-only black-box adversarial attack, where only final decisions are available to the adversary.

Adversarial Attack Speaker Recognition

Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images

2 code implementations30 Sep 2021 Yuyu Guo, Lei Bi, Dongming Wei, Liyun Chen, Zhengbin Zhu, Dagan Feng, Ruiyan Zhang, Qian Wang, Jinman Kim

In the first stage, we process the raw dense image to extract sparse landmarks to represent the target organ anatomical topology and discard the redundant information that is unnecessary for motion estimation.

Anatomy Motion Estimation +1

Digital Twins based Day-ahead Integrated Energy System Scheduling under Load and Renewable Energy Uncertainties

no code implementations29 Sep 2021 Minglei You, Qian Wang, Hongjian Sun, Ivan Castro, Jing Jiang

By constructing digital twins (DT) of an integrated energy system (IES), one can benefit from DT's predictive capabilities to improve coordinations among various energy converters, hence enhancing energy efficiency, cost savings and carbon emission reduction.


Multi-Modal MRI Reconstruction Assisted with Spatial Alignment Network

1 code implementation12 Aug 2021 Kai Xuan, Lei Xiang, Xiaoqian Huang, Lichi Zhang, Shu Liao, Dinggang Shen, Qian Wang

However, we find that the performance of the aforementioned multi-modal reconstruction can be negatively affected by subtle spatial misalignment between different modalities, which is actually common in clinical practice.

MRI Reconstruction

FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning

no code implementations8 Aug 2021 Shuang Dai, Fanlin Meng, Qian Wang, Xizhong Chen

Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumptions, can help to analyze electricity consumption behaviours of users and enable practical smart energy and smart grid applications.

Federated Learning Non-Intrusive Load Monitoring +1

Electrical peak demand forecasting- A review

no code implementations3 Aug 2021 Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen

To this end, this paper provides a timely and comprehensive overview of peak load demand forecast methods in the literature.


Intrusion Detection and Localization for Networked Embedded Control Systems

no code implementations17 Jun 2021 Vuk Lesi, Marcio Juliato, Shabbir Ahmed, Christopher Gutierrez, Qian Wang, Manoj Sastry

In this paper we present a physics-based Intrusion Detection System (IDS) aimed at increasing the security in control systems.

Intrusion Detection

CARTL: Cooperative Adversarially-Robust Transfer Learning

1 code implementation12 Jun 2021 Dian Chen, Hongxin Hu, Qian Wang, Yinli Li, Cong Wang, Chao Shen, Qi Li

In deep learning, a typical strategy for transfer learning is to freeze the early layers of a pre-trained model and fine-tune the rest of its layers on the target domain.

Adversarial Robustness Transfer Learning

FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework

no code implementations25 Apr 2021 Chen Zhao, Zhipeng Gao, Qian Wang, Kaile Xiao, Zijia Mo, M. Jamal Deen

With the proliferation of edge smart devices and the Internet of Vehicles (IoV) technologies, intelligent fatigue detection has become one of the most-used methods in our daily driving.

Federated Learning Model Optimization

How to distribute data across tasks for meta-learning?

no code implementations15 Mar 2021 Alexandru Cioba, Michael Bromberg, Qian Wang, Ritwik Niyogi, Georgios Batzolis, Jezabel Garcia, Da-Shan Shiu, Alberto Bernacchia

We show that: 1) If tasks are homogeneous, there is a uniform optimal allocation, whereby all tasks get the same amount of data; 2) At fixed budget, there is a trade-off between number of tasks and number of data points per task, with a unique solution for the optimum; 3) When trained separately, harder task should get more data, at the cost of a smaller number of tasks; 4) When training on a mixture of easy and hard tasks, more data should be allocated to easy tasks.

Few-Shot Image Classification Meta-Learning

A bottom-up quantification of flexibility potential from the thermal energy storage in electric space heating

no code implementations11 Mar 2021 Lars Herre, Behrouz Nourozi, Mohammad Reza Hesamzadeh, Qian Wang, Lennart Söder

To this end, dwellings with heat pumps and direct electric heaters are modeled as thermal energy storage equivalents that can be included in a linear two-stage problem formulation.

Modularity and Mutual Information in Networks: Two Sides of the Same Coin

no code implementations3 Mar 2021 Yongkang Guo, Zhihuan Huang, Yuqing Kong, Qian Wang

At a high level, we show the significance of community structure is equivalent to the amount of information contained in the network.

Community Detection Social and Information Networks

DeepCervix: A Deep Learning-based Framework for the Classification of Cervical Cells Using Hybrid Deep Feature Fusion Techniques

no code implementations24 Feb 2021 Md Mamunur Rahaman, Chen Li, YuDong Yao, Frank Kulwa, Xiangchen Wu, Xiaoyan Li, Qian Wang

Pap smear test is a widely performed screening technique for early detection of cervical cancer, whereas this manual screening method suffers from high false-positive results because of human errors.

Cell Segmentation Classification +1

Recent Advances in Adversarial Training for Adversarial Robustness

no code implementations2 Feb 2021 Tao Bai, Jinqi Luo, Jun Zhao, Bihan Wen, Qian Wang

Adversarial training is one of the most effective approaches defending against adversarial examples for deep learning models.

Adversarial Robustness

Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery

no code implementations21 Dec 2020 Qian Wang, Toby P. Breckon

Specifically, we formulate it as a 3D semantic segmentation problem to identify material types for all voxels based on which contraband materials can be detected.

3D Semantic Segmentation Computed Tomography (CT) +2

Data Augmentation with norm-VAE for Unsupervised Domain Adaptation

1 code implementation1 Dec 2020 Qian Wang, Fanlin Meng, Toby P. Breckon

As a result, our proposed methods (i. e. naive-SPL and norm-VAE-SPL) can achieve new state-of-the-art performance with the average accuracy of 93. 4% and 90. 4% on Office-Caltech and ImageCLEF-DA datasets, and comparable performance on Digits, Office31 and Office-Home datasets with the average accuracy of 97. 2%, 87. 6% and 67. 9% respectively.

Data Augmentation Image Classification +1

A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis

no code implementations29 Sep 2020 Yixin Li, Chen Li, Xiaoyan Li, Kai Wang, Md Mamunur Rahaman, Changhao Sun, Hao Chen, Xinran Wu, Hong Zhang, Qian Wang

In this review, we present a comprehensive overview of pathology image analysis based on the markov random fields (MRFs) and conditional random fields (CRFs), which are two popular random field models.

Collaborative Fairness in Federated Learning

1 code implementation27 Aug 2020 Lingjuan Lyu, Xinyi Xu, Qian Wang

In current deep learning paradigms, local training or the Standalone framework tends to result in overfitting and thus poor generalizability.

Fairness Federated Learning

Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders

no code implementations3 Aug 2020 Qian Wang, Toby P. Breckon

In this paper, we formulate this particular domain adaptation problem within a generalized zero-shot learning framework by treating the labelled source domain samples as semantic representations for zero-shot learning.

Domain Adaptation Generalized Zero-Shot Learning

Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery

no code implementations3 Aug 2020 Qian Wang, Neelanjan Bhowmik, Toby P. Breckon

X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on automatic prohibited item detection focus primarily on 2D X-ray imagery.

3D Object Detection Computed Tomography (CT) +3

Optimizing Information Freshness in Two-Hop Status Update Systems under a Resource Constraint

no code implementations6 Jul 2020 Yifan Gu, Qian Wang, He Chen, Yonghui Li, Branka Vucetic

We derive approximate closed-form expressions of the average AoI at the destination, and the average number of forwarding operations at the relay for the DTR policy, by modelling the tangled evolution of age at relay and destination as a Markov chain (MC).

Information Theory Networking and Internet Architecture Signal Processing Information Theory

mr2NST: Multi-Resolution and Multi-Reference Neural Style Transfer for Mammography

no code implementations25 May 2020 Sheng Wang, Jiayu Huo, Xi Ouyang, Jifei Che, Xuhua Ren, Zhong Xue, Qian Wang, Jie-Zhi Cheng

However, the image styles of different vendors are very distinctive, and there may exist domain gap among different vendors that could potentially compromise the universal applicability of one deep learning model.

Lesion Detection Style Transfer

A Self-ensembling Framework for Semi-supervised Knee Cartilage Defects Assessment with Dual-Consistency

1 code implementation19 May 2020 Jiayu Huo, Liping Si, Xi Ouyang, Kai Xuan, Weiwu Yao, Zhong Xue, Qian Wang, Dinggang Shen, Lichi Zhang

With dual-consistency checking of the attention in the lesion classification and localization, the two networks can gradually optimize the attention distribution and improve the performance of each other, whereas the training relies on partially labeled data only and follows the semi-supervised manner.

Classification General Classification +2

Cross-Domain Structure Preserving Projection for Heterogeneous Domain Adaptation

1 code implementation26 Apr 2020 Qian Wang, Toby P. Breckon

Heterogeneous Domain Adaptation (HDA) addresses the transfer learning problems where data from the source and target domains are of different modalities (e. g., texts and images) or feature dimensions (e. g., features extracted with different methods).

Domain Adaptation Transfer Learning

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

1 code implementation6 Apr 2020 Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen

In this review paper, we thus cover the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up.

Computed Tomography (CT)

Reducing Magnetic Resonance Image Spacing by Learning Without Ground-Truth

no code implementations27 Mar 2020 Kai Xuan, Liping Si, Lichi Zhang, Zhong Xue, Yining Jiao, Weiwu Yao, Dinggang Shen, Dijia Wu, Qian Wang

In this work, we propose a novel deep-learning-based super-resolution algorithm to generate high-resolution (HR) MR images with small slice spacing from low-resolution (LR) inputs of large slice spacing.


On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery

no code implementations27 Mar 2020 Qian Wang, Neelanjan Bhowmik, Toby P. Breckon

As the first attempt to use 3D CNN for volumetric 3D CT baggage security screening, we first evaluate different CNN architectures on the classification of isolated prohibited item volumes and compare against traditional methods which use hand-crafted features.

3D Object Detection Computed Tomography (CT) +3

Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world

3 code implementations12 Mar 2020 Ke Wu, Didier Darcet, Qian Wang, Didier Sornette

Japan and Italy are in serious situations with no short-term end to the outbreak to be expected.

Populations and Evolution Biological Physics Applications

A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image

1 code implementation CVPR 2020 Yuyu Guo, Lei Bi, Euijoon Ahn, Dagan Feng, Qian Wang, Jinman Kim

SVIN introduces dual networks: first is the spatiotemporal motion network that leverages the 3D convolutional neural network (CNN) for unsupervised parametric volumetric registration to derive spatiotemporal motion field from two-image volumes; the second is the sequential volumetric interpolation network, which uses the derived motion field to interpolate image volumes, together with a new regression-based module to characterize the periodic motion cycles in functional organ structures.


Publicly Verifiable Databases With All Efficient Updating Operations

no code implementations IEEE Transactions on Knowledge and Data Engineering 2020 Xiaofeng Chen, Hui Li, Jin Li, Qian Wang, Xinyi Huang, Willy Susilo, and Yang Xiang

As a result, it remains an open problem how to construct an efficient (and publicly verifiable) VDB scheme that can support all updating operations regardless of the manner of insertion.

Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions

no code implementations22 Feb 2020 Minghui Li, Sherman S. M. Chow, Shengshan Hu, Yuejing Yan, Chao Shen, Qian Wang

This paper proposes a new scheme for privacy-preserving neural network prediction in the outsourced setting, i. e., the server cannot learn the query, (intermediate) results, and the model.

Privacy Preserving

A Reference Architecture for Plausible Threat Image Projection (TIP) Within 3D X-ray Computed Tomography Volumes

1 code implementation15 Jan 2020 Qian Wang, Najla Megherbi, Toby P. Breckon

Threat Image Projection (TIP) is a technique used in X-ray security baggage screening systems that superimposes a threat object signature onto a benign X-ray baggage image in a plausible and realistic manner.

Computed Tomography (CT)

Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss

1 code implementation18 Nov 2019 Qian Wang, Toby P. Breckon

Automatic crowd behaviour analysis is an important task for intelligent transportation systems to enable effective flow control and dynamic route planning for varying road participants.

Crowd Counting Image Classification

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

1 code implementation18 Nov 2019 Qian Wang, Toby P. Breckon

Unsupervised domain adaptation aims to address the problem of classifying unlabeled samples from the target domain whilst labeled samples are only available from the source domain and the data distributions are different in these two domains.

Clustering Structured Prediction +1

Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection

no code implementations29 Oct 2019 Lingchen Zhao, Shengshan Hu, Qian Wang, Jianlin Jiang, Chao Shen, Xiangyang Luo, Pengfei Hu

Collaborative learning allows multiple clients to train a joint model without sharing their data with each other.

An End-to-End Network for Co-Saliency Detection in One Single Image

no code implementations25 Oct 2019 Yuanhao Yue, Qin Zou, Hongkai Yu, Qian Wang, Zhongyuan Wang, Song Wang

Co-saliency detection within a single image is a common vision problem that has received little attention and has not yet been well addressed.

Clustering Co-Salient Object Detection +1

NCLS: Neural Cross-Lingual Summarization

1 code implementation IJCNLP 2019 Junnan Zhu, Qian Wang, Yining Wang, Yu Zhou, Jiajun Zhang, Shaonan Wang, Cheng-qing Zong

Moreover, we propose to further improve NCLS by incorporating two related tasks, monolingual summarization and machine translation, into the training process of CLS under multi-task learning.

Machine Translation Multi-Task Learning +2

Synthesis and Inpainting-Based MR-CT Registration for Image-Guided Thermal Ablation of Liver Tumors

no code implementations30 Jul 2019 Dongming Wei, Sahar Ahmad, Jiayu Huo, Wen Peng, Yunhao Ge, Zhong Xue, Pew-Thian Yap, Wentao Li, Dinggang Shen, Qian Wang

Then, an unsupervised registration network is used to efficiently align the pre-procedural CT (pCT) with the inpainted iCT (inpCT) image.

Image Registration

Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis

no code implementations7 Jul 2019 Dong Nie, Lei Xiang, Qian Wang, Dinggang Shen

To address this issue, we propose a simple but effective strategy, that is, we propose a dual-discriminator (dual-D) adversarial learning system, in which, a global-D is used to make an overall evaluation for the synthetic image, and a local-D is proposed to densely evaluate the local regions of the synthetic image.

Image Generation

Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation

no code implementations21 May 2019 Xuhua Ren, Lichi Zhang, Sahar Ahmad, Dong Nie, Fan Yang, Lei Xiang, Qian Wang, Dinggang Shen

In this paper, we propose to decompose the single segmentation task into three subsequent sub-tasks, including (1) pixel-wise image segmentation, (2) prediction of the class labels of the objects within the image, and (3) classification of the scene the image belonging to.

Brain Tumor Segmentation Image Segmentation +3

DLIMD: Dictionary Learning based Image-domain Material Decomposition for spectral CT

no code implementations6 May 2019 Weiwen Wu, Haijun Yu, Peijun Chen, Fulin Luo, Fenglin Liu, Qian Wang, Yining Zhu, Yanbo Zhang, Jian Feng, Hengyong Yu

Second, we employ the direct inversion (DI) method to obtain initial material decomposition results, and a set of image patches are extracted from the mode-1 unfolding of normalized material image tensor to train a united dictionary by the K-SVD technique.

Computed Tomography (CT) Dictionary Learning +1

Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition

1 code implementation25 Mar 2019 Qian Wang, Penghui Bu, Toby P. Breckon

Unsupervised domain adaptation aims to transfer knowledge from a source domain to a target domain so that the target domain data can be recognized without any explicit labelling information for this domain.

domain classification Generalized Zero-Shot Learning +2

Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks

2 code implementations6 Mar 2019 Qin Zou, Hanwen Jiang, Qiyu Dai, Yuanhao Yue, Long Chen, Qian Wang

Specifically, information of each frame is abstracted by a CNN block, and the CNN features of multiple continuous frames, holding the property of time-series, are then fed into the RNN block for feature learning and lane prediction.

Lane Detection Time Series +1

Automated Segmentation of the Optic Disk and Cup using Dual-Stage Fully Convolutional Networks

no code implementations13 Feb 2019 Lei Bi, Yuyu Guo, Qian Wang, Dagan Feng, Michael Fulham, Jinman Kim

Our approach leverages deep residual architectures and FCNs and learns and infers the location of the optic cup and disk in a step-wise manner with fine-grained details.

Segmentation Test

Privacy-Preserving Collaborative Deep Learning with Unreliable Participants

no code implementations25 Dec 2018 Lingchen Zhao, Qian Wang, Qin Zou, Yan Zhang, Yanjiao Chen

With powerful parallel computing GPUs and massive user data, neural-network-based deep learning can well exert its strong power in problem modeling and solving, and has archived great success in many applications such as image classification, speech recognition and machine translation etc.

Image Classification Machine Translation +3

Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning

1 code implementation3 Dec 2018 Zhibo Wang, Mengkai Song, Zhifei Zhang, Yang song, Qian Wang, Hairong Qi

Although the state-of-the-art attacking techniques that incorporated the advance of Generative adversarial networks (GANs) could construct class representatives of the global data distribution among all clients, it is still challenging to distinguishably attack a specific client (i. e., user-level privacy leakage), which is a stronger privacy threat to precisely recover the private data from a specific client.

Edge-computing Federated Learning +1

A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks

1 code implementation20 Nov 2018 Qian Wang, Ning Jia, Toby P. Breckon

Recent studies on multi-label image classification have focused on designing more complex architectures of deep neural networks such as the use of attention mechanisms and region proposal networks.

Classification Data Augmentation +3

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.

Brain Tumor Segmentation Survival Prediction +1

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

1 code implementation1 Nov 2018 Qin Zou, Yanling Wang, Qian Wang, Yi Zhao, Qingquan Li

Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted by a convolutional neural network and a recurrent neural network.

Gait Recognition Person Identification

Block Matching Frame based Material Reconstruction for Spectral CT

no code implementations22 Oct 2018 Weiwen Wu, Qian Wang, Fenglin Liu, Yining Zhu, Hengyong Yu

Spectral computed tomography (CT) has a great potential in material identification and decomposition.

Computed Tomography (CT)

Supervised and Semi-Supervised Deep Neural Networks for CSI-Based Authentication

no code implementations25 Jul 2018 Qian Wang, Hang Li, Zhi Chen, Dou Zhao, Shuang Ye, Jiansheng Cai

In addition, we propose to use the convolutional recurrent neural network (CRNN)---a combination of the CNN and the RNN---to learn local and contextual information in CSI for user authentication.

Non-local Low-rank Cube-based Tensor Factorization for Spectral CT Reconstruction

no code implementations24 Jul 2018 Weiwen Wu, Fenglin Liu, Yanbo Zhang, Qian Wang, Hengyong Yu

Then, as a new regularizer, Kronecker-Basis-Representation (KBR) tensor factorization is employed into a basic spectral CT reconstruction model to enhance the ability of extracting image features and protecting spatial edges, generating the non-local low-rank cube-based tensor factorization (NLCTF) method.

Clustering Computed Tomography (CT)

Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity

no code implementations28 Apr 2018 Xiaohuan Cao, Jianhua Yang, Li Wang, Zhong Xue, Qian Wang, Dinggang Shen

In this paper, we propose to train a non-rigid inter-modality image registration network, which can directly predict the transformation field from the input multimodal images, such as CT and MR images.

Image Registration

Medical Image Synthesis with Deep Convolutional Adversarial Networks

1 code implementation IEEE Transactions on Biomedical Engineering 2018 Dong Nie, Roger Trullo, Jun Lian, Li Wang, Caroline Petitjean, Su Ruan, Qian Wang, and Dinggang Shen, Fellow, IEEE

To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN.

Image Generation

Low-dose spectral CT reconstruction using L0 image gradient and tensor dictionary

no code implementations13 Dec 2017 Weiwen Wu, Yanbo Zhang, Qian Wang, Fenglin Liu, Peijun Chen, Hengyong Yu

The L0TDL method inherits the advantages of tensor dictionary learning (TDL) by employing the similarity of spectral CT images.

Computed Tomography (CT) Dictionary Learning +1

Multi-Label Zero-Shot Human Action Recognition via Joint Latent Ranking Embedding

no code implementations15 Sep 2017 Qian Wang, Ke Chen

Our framework holistically tackles the issue of unknown temporal boundaries between different actions for multi-label learning and exploits the side information regarding the semantic relationship between different human actions for knowledge transfer.

Action Recognition Multi-Label Learning +3