Search Results for author: Ying Wang

Found 83 papers, 20 papers with code

Asymptotically Efficient Quasi-Newton Type Identification with Quantized Observations Under Bounded Persistent Excitations

no code implementations10 Sep 2023 Ying Wang, Yanlong Zhao, Ji-Feng Zhang

This paper is concerned with the optimal identification problem of dynamical systems in which only quantized output observations are available under the assumption of fixed thresholds and bounded persistent excitations.

Federated Learning in Big Model Era: Domain-Specific Multimodal Large Models

no code implementations22 Aug 2023 Zengxiang Li, Zhaoxiang Hou, Hui Liu, Ying Wang, Tongzhi Li, Longfei Xie, Chao Shi, Chengyi Yang, Weishan Zhang, Zelei Liu, Liang Xu

Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management.

Federated Learning Management

A Survey on Fairness in Large Language Models

no code implementations20 Aug 2023 Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang

Then, for large-scale LLMs, we introduce recent fairness research, including fairness evaluation, reasons for bias, and debiasing methods.


Exploring Winograd Convolution for Cost-effective Neural Network Fault Tolerance

no code implementations16 Aug 2023 Xinghua Xue, Cheng Liu, Bo Liu, Haitong Huang, Ying Wang, Tao Luo, Lei Zhang, Huawei Li, Xiaowei Li

When it is applied on fault-tolerant neural networks enhanced with fault-aware retraining and constrained activation functions, the resulting model accuracy generally shows significant improvement in presence of various faults.

From Ambiguity to Explicitness: NLP-Assisted 5G Specification Abstraction for Formal Analysis

no code implementations7 Aug 2023 Shiyu Yuan, Jingda Yang, Sudhanshu Arya, Carlo Lipizzi, Ying Wang

Our work is proof of concept for an efficient procedure in performing formal analysis for largescale complicate specification and protocol analysis, especially for 5G and nextG communications.

Distributed 3D-Beam Reforming for Hovering-Tolerant UAVs Communication over Coexistence: A Deep-Q Learning for Intelligent Space-Air-Ground Integrated Networks

no code implementations18 Jul 2023 Sudhanshu Arya, Yifeng Peng, Jingda Yang, Ying Wang

By augmenting the system with the impairments due to hovering and rotational motion, we show that the proposed DQN algorithm can reform the beam in real-time with negligible error.

Q-Learning Reinforcement Learning (RL)

MRFI: An Open Source Multi-Resolution Fault Injection Framework for Neural Network Processing

1 code implementation20 Jun 2023 Haitong Huang, Cheng Liu, Xinghua Xue, Ying Wang, Huawei Li, Xiaowei Li

It enables users to modify an independent fault configuration file rather than neural network models for the fault injection and vulnerability analysis.

ChipGPT: How far are we from natural language hardware design

no code implementations23 May 2023 Kaiyan Chang, Ying Wang, Haimeng Ren, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li

As large language models (LLMs) like ChatGPT exhibited unprecedented machine intelligence, it also shows great performance in assisting hardware engineers to realize higher-efficiency logic design via natural language interaction.

NLP-based Cross-Layer 5G Vulnerabilities Detection via Fuzzing Generated Run-Time Profiling

no code implementations14 May 2023 Zhuzhu Wang, Ying Wang

The effectiveness and efficiency of 5G software stack vulnerability and unintended behavior detection are essential for 5G assurance, especially for its applications in critical infrastructures.

Radar Altimeter Redesign for Multi-Stage Interference Risk Mitigation in 5G and Beyond

no code implementations9 May 2023 Jarret Rock, Ying Wang

The radar altimeter is installed on most 14 CFR Pt 25 category aircraft, which are applicable to passenger travel and represent most airline traffic.

Location Tracking for Reconfigurable Intelligent Surfaces Aided Vehicle Platoons: Diverse Sparsities Inspired Approaches

no code implementations7 May 2023 Yuanbin Chen, Ying Wang, Xufeng Guo, Zhu Han, Ping Zhang

In this paper, we investigate the employment of reconfigurable intelligent surfaces (RISs) into vehicle platoons, functioning in tandem with a base station (BS) in support of the high-precision location tracking.

Bayesian Inference Philosophy

Bayesian Inference-assisted Machine Learning for Near Real-Time Jamming Detection and Classification in 5G New Radio (NR)

no code implementations26 Apr 2023 Shashank Jere, Ying Wang, Ishan Aryendu, Shehadi Dayekh, Lingjia Liu

The increased flexibility and density of spectrum access in 5G New Radio (NR) has made jamming detection and classification a critical research area.

Bayesian Inference Time Series

AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+

1 code implementation14 Mar 2023 Xiao Wang, Ying Wang, Ziwei Xuan, Guo-Jun Qi

A criterion in unsupervised pretraining is the pretext task needs to be sufficiently hard to prevent the transformer encoder from learning trivial low-level features not generalizable well to downstream tasks.

Transfer Learning

Variation Enhanced Attacks Against RRAM-based Neuromorphic Computing System

no code implementations20 Feb 2023 Hao Lv, Bing Li, Lei Zhang, Cheng Liu, Ying Wang

The RRAM-based neuromorphic computing system has amassed explosive interests for its superior data processing capability and energy efficiency than traditional architectures, and thus being widely used in many data-centric applications.

Adversarial Attack

Recursive Identification of Set-Valued Systems under Uniform Persistent Excitations

no code implementations4 Dec 2022 Jieming Ke, Ying Wang, Yanlong Zhao, Ji-Feng Zhang

This paper studies the control-oriented identification problem of set-valued moving average systems with uniform persistent excitations and observation noises.

A Node-collaboration-informed Graph Convolutional Network for Precise Representation to Undirected Weighted Graphs

no code implementations30 Nov 2022 Ying Wang, Ye Yuan, Xin Luo

Based on this idea, a Node-collaboration-informed Graph Convolutional Network (NGCN) is proposed with three-fold ideas: a) Learning latent collaborative information from the interaction of node pairs via a node-collaboration module; b) Building the residual connection and weighted representation propagation to obtain high representation capacity; and c) Implementing the model optimization in an end-to-end fashion to achieve precise representation to the target UWG.

Model Optimization Representation Learning

Representation Learning for Continuous Action Spaces is Beneficial for Efficient Policy Learning

no code implementations23 Nov 2022 Tingting Zhao, Ying Wang, Wei Sun, Yarui Chen, Gang Niub, Masashi Sugiyama

Meanwhile, we divide the whole learning task into learning with the large-scale representation models in an unsupervised manner and learning with the small-scale policy model in the RL manner. The small policy model facilitates policy learning, while not sacrificing generalization and expressiveness via the large representation model.

reinforcement-learning Reinforcement Learning (RL) +1

Sybil-Proof Diffusion Auction in Social Networks

no code implementations3 Nov 2022 Hongyin Chen, Xiaotie Deng, Ying Wang, Yue Wu, Dengji Zhao

A diffusion auction is a market to sell commodities over a social network, where the challenge is to incentivize existing buyers to invite their neighbors in the network to join the market.

Balancing Utility and Fairness in Submodular Maximization (Technical Report)

1 code implementation2 Nov 2022 Yanhao Wang, Yuchen Li, Francesco Bonchi, Ying Wang

Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications -- including data summarization, influence maximization, and recommendation.

Combinatorial Optimization Data Summarization +1

Statistical Modeling of Soft Error Influence on Neural Networks

no code implementations12 Oct 2022 Haitong Huang, Xinghua Xue, Cheng Liu, Ying Wang, Tao Luo, Long Cheng, Huawei Li, Xiaowei Li

Prior work mainly rely on fault simulation to analyze the influence of soft errors on NN processing.


Prompt Tuning with Soft Context Sharing for Vision-Language Models

1 code implementation29 Aug 2022 Kun Ding, Ying Wang, Pengzhang Liu, Qiang Yu, Haojian Zhang, Shiming Xiang, Chunhong Pan

Inspired by the fact that modeling task relationships by multi-task learning can usually boost performance, we propose a novel method SoftCPT (Soft Context Sharing for Prompt Tuning) to fine-tune pre-trained vision-language models on multiple target few-shot tasks, simultaneously.

Few-Shot Learning Multi-Task Learning

Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps

no code implementations16 Aug 2022 Kun Qiu, Harry Chang, Ying Wang, Xiahui Yu, Wenjun Zhu, Yingqi Liu, Jianwei Ma, Weigang Li, Xiaobo Liu, Shuo Dai

Sophisticated traffic analytics, such as the encrypted traffic analytics and unknown malware detection, emphasizes the need for advanced methods to analyze the network traffic.

Malware Detection Traffic Classification

GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks

1 code implementation SIGKDD 2022 Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang

Based on the pre-trained model, we propose the graph prompting function to modify the standalone node into a token pair, and reformulate the downstream node classification looking the same as edge prediction.

Few-Shot Learning Node Classification +3

DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis

no code implementations13 Aug 2022 Jingliang Li, Zhengda Lu, Yiqun Wang, Ying Wang, Jun Xiao

To mine the information in probability volume, we creatively synthesize the source depths by splattering the probability volume and depth hypotheses to source views.

Inverted Semantic-Index for Image Retrieval

no code implementations25 Jun 2022 Ying Wang

We then propose a merging and splitting method to solve the problem that the number of partitions is unchangeable in the inverted semantic-index.

Clustering Image Classification +3

Reconfigurable Intelligent Surface (RIS)-aided Vehicular Networks: Their Protocols, Resource Allocation, and Performance

no code implementations5 Mar 2022 Yuanbin Chen, Ying Wang, Jiayi Zhang, Ping Zhang, Lajos Hanzo

Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving.

Autonomous Driving

Winograd Convolution: A Perspective from Fault Tolerance

no code implementations17 Feb 2022 Xinghua Xue, Haitong Huang, Cheng Liu, Ying Wang, Tao Luo, Lei Zhang

Winograd convolution is originally proposed to reduce the computing overhead by converting multiplication in neural network (NN) with addition via linear transformation.

Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

no code implementations17 Feb 2022 Jiaxu Li, Yin Xu, Ying Wang, Meng Li, Jinghan He, Chen-Ching Liu, Kevin P. Schneider

In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed.

Dual-Flattening Transformers through Decomposed Row and Column Queries for Semantic Segmentation

no code implementations22 Jan 2022 Ying Wang, Chiuman Ho, Wenju Xu, Ziwei Xuan, Xudong Liu, Guo-Jun Qi

We propose a Dual-Flattening Transformer (DFlatFormer) to enable high-resolution output by reducing complexity to $\mathcal{O}(hw(H+W))$ that is multiple orders of magnitude smaller than the naive dense transformer.

Semantic Segmentation

DDU-Net: Dual-Decoder-U-Net for Road Extraction Using High-Resolution Remote Sensing Images

no code implementations18 Jan 2022 Ying Wang, Yuexing Peng, Xinran Liu, Wei Li, George C. Alexandropoulos, Junchuan Yu, Daqing Ge, Wei Xiang

Extracting roads from high-resolution remote sensing images (HRSIs) is vital in a wide variety of applications, such as autonomous driving, path planning, and road navigation.

Autonomous Driving

Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data

1 code implementation30 Dec 2021 Shenwang Jiang, Jianan Li, Ying Wang, Bo Huang, Zhang Zhang, Tingfa Xu

In practice, however, biased samples with corrupted labels and of tailed classes commonly co-exist in training data.


Hard Sample Aware Noise Robust Learning for Histopathology Image Classification

1 code implementation5 Dec 2021 Chuang Zhu, Wenkai Chen, Ting Peng, Ying Wang, Mulan Jin

In this work, we introduce a novel hard sample aware noise robust learning method for histopathology image classification.

Classification Learning with noisy labels

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides

1 code implementation4 Dec 2021 Feng Xu, Chuang Zhu, Wenqi Tang, Ying Wang, Yu Zhang, Jie Li, Hongchuan Jiang, Zhongyue Shi, Jun Liu, Mulan Jin

Conclusion: Our study provides a novel DL-based biomarker on primary tumor CNB slides to predict the metastatic status of ALN preoperatively for patients with EBC.

Multiple Instance Learning Specificity +1

Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism

no code implementations1 Dec 2021 Minghan Fu, Yanhua Duan, Zhaoping Cheng, Wenjian Qin, Ying Wang, Dong Liang, Zhanli Hu

The derived architecture is referred to as the Teacher-Student Consistency Network (TSC-Net), which consists of the teacher network and the student network with identical architecture.

Contrastive Learning Image Denoising +1

PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds

no code implementations28 Nov 2021 Jie Wang, Jianan Li, Lihe Ding, Ying Wang, Tingfa Xu

Fine-grained geometry, captured by aggregation of point features in local regions, is crucial for object recognition and scene understanding in point clouds.

3D Shape Classification graph construction +3

Perceptual Consistency in Video Segmentation

no code implementations24 Oct 2021 Yizhe Zhang, Shubhankar Borse, Hong Cai, Ying Wang, Ning Bi, Xiaoyun Jiang, Fatih Porikli

More specifically, by measuring the perceptual consistency between the predicted segmentation and the available ground truth on a nearby frame and combining it with the segmentation confidence, we can accurately assess the classification correctness on each pixel.

Semantic Segmentation Video Segmentation +1

Pyramid Correlation based Deep Hough Voting for Visual Object Tracking

no code implementations15 Oct 2021 Ying Wang, Tingfa Xu, Jianan Li, Shenwang Jiang, Junjie Chen

Through experiments we find that, without regression, the performance could be equally promising as long as we delicately design the network to suit the training objective.

regression Visual Object Tracking

On the Scheduling Policy for Multi-process WNCS under Edge Computing

no code implementations26 Sep 2021 Yifei Qiu, Shaohua Wu, Ying Wang

The monotonicity of the value function in MDP is characterized and then used to show the threshold structure properties of the optimal scheduling policy.

Edge-computing Scheduling

A Semantic Indexing Structure for Image Retrieval

no code implementations14 Sep 2021 Ying Wang, Tingzhen Liu, Zepeng Bu, YuHui Huang, Lizhong Gao, Qiao Wang

In large-scale image retrieval, many indexing methods have been proposed to narrow down the searching scope of retrieval.

Image Retrieval Retrieval +2

R2F: A Remote Retraining Framework for AIoT Processors with Computing Errors

no code implementations7 Jul 2021 Dawen Xu, Meng He, Cheng Liu, Ying Wang, Long Cheng, Huawei Li, Xiaowei Li, Kwang-Ting Cheng

It takes the remote AIoT processor with soft errors in the training loop such that the on-site computing errors can be learned with the application data on the server and the retrained models can be resilient to the soft errors.

HAN: An Efficient Hierarchical Self-Attention Network for Skeleton-Based Gesture Recognition

no code implementations25 Jun 2021 Jianbo Liu, Ying Wang, Shiming Xiang, Chunhong Pan

Previous methods for skeleton-based gesture recognition mostly arrange the skeleton sequence into a pseudo picture or spatial-temporal graph and apply deep Convolutional Neural Network (CNN) or Graph Convolutional Network (GCN) for feature extraction.

Gesture Recognition

InverseForm: A Loss Function for Structured Boundary-Aware Segmentation

1 code implementation CVPR 2021 Shubhankar Borse, Ying Wang, Yizhe Zhang, Fatih Porikli

We present a novel boundary-aware loss term for semantic segmentation using an inverse-transformation network, which efficiently learns the degree of parametric transformations between estimated and target boundaries.

Ranked #3 on Semantic Segmentation on Cityscapes test (using extra training data)

Semantic Segmentation

Damage accumulation during high temperature fatigue of Ti/SiC$_f$ metal matrix composites under different stress amplitudes

no code implementations26 Feb 2021 Ying Wang, Xu Xu, Wenxia Zhao, Nan Li, Samuel A. McDonald, Yuan Chai, Michael Atkinson, Katherine J. Dobson, Stefan Michalik, Yingwei Fan, Philip J. Withers, Xiaorong Zhou, Timothy L. Burnett

The three-dimensional morphology of the crack and fibre fractures has been mapped by CT. During stable growth, matrix cracking dominates with the crack deflecting (by 50-100 $\mu$m in height) when bypassing bridging fibres.

Computed Tomography (CT) X-Ray Diffraction (XRD) Materials Science Applied Physics

Hero: On the Chaos When PATH Meets Modules

no code implementations24 Feb 2021 Ying Wang, Liang Qiao, Chang Xu, Yepang Liu, Shing-Chi Cheung, Na Meng, Hai Yu, Zhiliang Zhu

The results showed that \textsc{Hero} achieved a high detection rate of 98. 5\% on a DM issue benchmark and found 2, 422 new DM issues in 2, 356 popular Golang projects.

Software Engineering

Electroabsorption in gated GaAs nanophotonic waveguides

no code implementations11 Feb 2021 Ying Wang, Ravitej Uppu, Xiaoyan Zhou, Camille Papon, Sven Scholz, Andreas D. Wieck, Arne Ludwig, Peter Lodahl, Leonardo Midolo

We report on the analysis of electroabsorption in thin GaAs/Al$_{0. 3}$Ga$_{0. 7}$As nanophotonic waveguides with an embedded $p$-$i$-$n$ junction.

Optics Materials Science Quantum Physics

SWA Object Detection

2 code implementations23 Dec 2020 Haoyang Zhang, Ying Wang, Feras Dayoub, Niko Sünderhauf

In this technique report, we systematically investigate the effects of applying SWA to object detection as well as instance segmentation.

Instance Segmentation object-detection +2

VC-Net: Deep Volume-Composition Networks for Segmentation and Visualization of Highly Sparse and Noisy Image Data

no code implementations14 Sep 2020 Yifan Wang, Guoli Yan, Haikuan Zhu, Sagar Buch, Ying Wang, Ewart Mark Haacke, Jing Hua, Zichun Zhong

A multi-stream convolutional neural network is proposed to learn the 3D volume and 2D MIP features respectively and then explore their inter-dependencies in a joint volume-composition embedding space by unprojecting the MIP features into 3D volume embedding space.

VarifocalNet: An IoU-aware Dense Object Detector

3 code implementations CVPR 2021 Haoyang Zhang, Ying Wang, Feras Dayoub, Niko Sünderhauf

In this paper, we propose to learn an Iou-aware Classification Score (IACS) as a joint representation of object presence confidence and localization accuracy.

General Classification Object Detection

Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet

2 code implementations29 Jun 2020 Chuang Zhu, Ke Mei, Ting Peng, Yihao Luo, Jun Liu, Ying Wang, Mulan Jin

The automatic and objective medical diagnostic model can be valuable to achieve early cancer detection, and thus reducing the mortality rate.

Tumor Segmentation

Bayesian Bits: Unifying Quantization and Pruning

1 code implementation NeurIPS 2020 Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling

We introduce Bayesian Bits, a practical method for joint mixed precision quantization and pruning through gradient based optimization.


Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware

no code implementations ICLR 2020 Xiandong Zhao, Ying Wang, Xuyi Cai, Cheng Liu, Lei Zhang

With the proliferation of specialized neural network processors that operate on low-precision integers, the performance of Deep Neural Network inference becomes increasingly dependent on the result of quantization.

object-detection Object Detection +1

Combining GHOST and Casper

6 code implementations6 Mar 2020 Vitalik Buterin, Diego Hernandez, Thor Kamphefner, Khiem Pham, Zhi Qiao, Danny Ryan, Juhyeok Sin, Ying Wang, Yan X Zhang

We present "Gasper," a proof-of-stake-based consensus protocol, which is an idealized version of the proposed Ethereum 2. 0 beacon chain.

Cryptography and Security 68W15

An Iterative Heuristic Method to Determine Radial Topology for Distribution System Restoration

no code implementations11 Dec 2019 Jiayu Liu, Qiqi Zhang, Jiaxu Li, Ying Wang

The case studies indicate that the proposed method can determine radial topology in a few seconds and ensure the restoration capacity.

LiDAR Iris for Loop-Closure Detection

no code implementations9 Dec 2019 Ying Wang, Zezhou Sun, Cheng-Zhong Xu, Sanjay Sarma, Jian Yang, Hui Kong

In this paper, a global descriptor for a LiDAR point cloud, called LiDAR Iris, is proposed for fast and accurate loop-closure detection.

Loop Closure Detection

Breast Anatomy Enriched Tumor Saliency Estimation

no code implementations23 Oct 2019 Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang

Then we refine the layers by integrating a non-semantic breast anatomy model to solve the problems of incomplete mammary layers.

Anatomy Saliency Prediction

Accelerating Generative Neural Networks on Unmodified Deep Learning Processors -- A Software Approach

2 code implementations3 Jul 2019 Dawen Xu, Ying Wang, Kaijie Tu, Cheng Liu, Bingsheng He, Lei Zhang

Generative neural network is a new category of neural networks and it has been widely utilized in applications such as content generation, unsupervised learning, segmentation and pose estimation.

Pose Estimation

Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants

1 code implementation24 Jun 2019 Yalong Liu, Jie Li, Ying Wang, Miaomiao Wang, Xianjun Li, Zhicheng Jiao, Jian Yang, Xingbo Gao

In this paper, we construct an efficient two-stage PWML semantic segmentation network based on the characteristics of the lesion, called refined segmentation R-CNN (RS RCNN).

Image Segmentation Lesion Segmentation +2

Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling

no code implementations18 Jun 2019 Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang

First, we model breast anatomy and decompose breast ultrasound image into layers using Neutro-Connectedness; then utilize the layers to generate the foreground and background maps; and finally propose a novel objective function to estimate the tumor saliency by integrating the foreground map, background map, adaptive center bias, and region-based correlation cues.

Anatomy Saliency Prediction

Inpatient2Vec: Medical Representation Learning for Inpatients

no code implementations18 Apr 2019 Ying Wang, Xiao Xu, Tao Jin, Xiang Li, Guotong Xie, Jian-Min Wang

In addition, for unordered medical activity set, existing medical RL methods utilize a simple pooling strategy, which would result in indistinguishable contributions among the activities for learning.

Representation Learning Semantic Similarity +1

A Hybrid Framework for Tumor Saliency Estimation

no code implementations27 Jun 2018 Fei Xu, Min Xian, Yingtao Zhang, Kuan Huang, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang

Automatic tumor segmentation of breast ultrasound (BUS) image is quite challenging due to the complicated anatomic structure of breast and poor image quality.

Saliency Prediction Tumor Segmentation

BUSIS: A Benchmark for Breast Ultrasound Image Segmentation

1 code implementation9 Jan 2018 Min Xian, Yingtao Zhang, H. D. Cheng, Fei Xu, Kuan Huang, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang

Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Comput-er-Aided Diagnosis (CAD) systems.

Image Segmentation Tumor Segmentation

Review. Machine learning techniques for traffic sign detection

no code implementations12 Dec 2017 Rinat Mukhometzianov, Ying Wang

An automatic road sign detection system localizes road signs from within images captured by an on-board camera of a vehicle, and support the driver to properly ride the vehicle.

BIG-bench Machine Learning Traffic Sign Detection

Restricting Greed in Training of Generative Adversarial Network

no code implementations28 Nov 2017 Haoxuan You, Zhicheng Jiao, Haojun Xu, Jie Li, Ying Wang, Xinbo Gao

Generative adversarial network (GAN) has gotten wide re-search interest in the field of deep learning.

10,000+ Times Accelerated Robust Subset Selection (ARSS)

no code implementations12 Sep 2014 Feiyun Zhu, Bin Fan, Xinliang Zhu, Ying Wang, Shiming Xiang, Chunhong Pan

Subset selection from massive data with noised information is increasingly popular for various applications.

Action Recognition Collaborative Filtering +16

Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity

no code implementations2 Sep 2014 Feiyun Zhu, Ying Wang, Bin Fan, Gaofeng Meng, Chunhong Pan

Based on this observation, we exploit a learning-based sparsity method to simultaneously learn the HU results and a sparse guidance map.

Hyperspectral Unmixing

Structured Sparse Method for Hyperspectral Unmixing

no code implementations19 Mar 2014 Feiyun Zhu, Ying Wang, Shiming Xiang, Bin Fan, Chunhong Pan

With this constraint, our method can learn a compact space, where highly similar pixels are grouped to share correlated sparse representations.

Hyperspectral Unmixing

Spectral Unmixing via Data-guided Sparsity

no code implementations13 Mar 2014 Feiyun Zhu, Ying Wang, Bin Fan, Gaofeng Meng, Shiming Xiang, Chunhong Pan

Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral analysis, visualization and understanding.

Hyperspectral Unmixing

Robust Hyperspectral Unmixing with Correntropy based Metric

no code implementations31 May 2013 Ying Wang, Chunhong Pan, Shiming Xiang, Feiyun Zhu

In addition, with sparsity constraints, our model can naturally generate sparse abundances.

Hyperspectral Unmixing

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