Search Results for author: Cong Wang

Found 79 papers, 24 papers with code

基于BiLSTM-CRF的社会突发事件研判方法(Social Emergency Event Judgement based on BiLSTM-CRF)

no code implementations CCL 2020 Huijun Hu, Cong Wang, Jianhua Dai, Maofu Liu

社会突发事件的分类和等级研判作为应急处置中的一环, 其重要性不言而喻。然而, 目前研究多数采用人工或规则的方法识别证据进行研判, 由于社会突发事件的构成的复杂性和语言描述的灵活性, 这对于研判证据识别有很大局限性。本文参考“事件抽取”思想, 事件类型和研判证据作为事件中元素, 以BiLSTM-CRF方法细粒度的识别, 并将二者结合, 分类结果作为等级研判的输入, 识别出研判证据。最终将识别结果结合注意力机制进行等级研判, 通过对研判证据的精准识别从而来增强等级研判的准确性。实验表明, 相比人工或规则识别研判证据, 本文提出的方法有着更好的鲁棒性, 社会突发事件研判时也达到了较好的效果。 关键词:事件分类 ;研判证据识别 ;等级研判 ;BiLSTM-CRF

How Powerful Potential of Attention on Image Restoration?

no code implementations15 Mar 2024 Cong Wang, Jinshan Pan, Yeying Jin, Liyan Wang, Wei Wang, Gang Fu, Wenqi Ren, Xiaochun Cao

Our designs provide a closer look at the attention mechanism and reveal that some simple operations can significantly affect the model performance.

Image Restoration

Phrase Grounding-based Style Transfer for Single-Domain Generalized Object Detection

no code implementations2 Feb 2024 Hao Li, Wei Wang, Cong Wang, Zhigang Luo, Xinwang Liu, Kenli Li, Xiaochun Cao

Single-domain generalized object detection aims to enhance a model's generalizability to multiple unseen target domains using only data from a single source domain during training.

object-detection Object Detection +2

Detection and Mitigation of Position Spoofing Attacks on Cooperative UAV Swarm Formations

no code implementations6 Dec 2023 Siguo Bi, Kai Li, Shuyan Hu, Wei Ni, Cong Wang, Xin Wang

Detecting spoofing attacks on the positions of unmanned aerial vehicles (UAVs) within a swarm is challenging.

Position

DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance

no code implementations5 Dec 2023 Cong Wang, Jiaxi Gu, Panwen Hu, Songcen Xu, Hang Xu, Xiaodan Liang

Especially for fidelity, our model has a powerful image retention ability and delivers the best results in UCF101 compared to other image-to-video models to our best knowledge.

Image to Video Generation

Augmenting x-ray single particle imaging reconstruction with self-supervised machine learning

1 code implementation28 Nov 2023 Zhantao Chen, Cong Wang, Mingye Gao, Chun Hong Yoon, Jana B. Thayer, Joshua J. Turner

The development of X-ray Free Electron Lasers (XFELs) has opened numerous opportunities to probe atomic structure and ultrafast dynamics of various materials.

DualMatch: Robust Semi-Supervised Learning with Dual-Level Interaction

1 code implementation25 Oct 2023 Cong Wang, Xiaofeng Cao, Lanzhe Guo2, Zenglin Shi

In this paper, we propose a novel SSL method called DualMatch, in which the class prediction jointly invokes feature embedding in a dual-level interaction manner.

Data Augmentation

Adaptive Gating in Mixture-of-Experts based Language Models

no code implementations11 Oct 2023 Jiamin Li, Qiang Su, Yitao Yang, Yimin Jiang, Cong Wang, Hong Xu

Existing MoE model adopts a fixed gating network where each token is computed by the same number of experts.

Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

1 code implementation10 Oct 2023 Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, Wei Yang

Specifically, in the first stage, we design a simple prior conditional diffusion model that predicts the global features of the target image by mining the global alignment relationship between pose coordinates and image appearance.

Image Generation

Self-supervised Learning for Anomaly Detection in Computational Workflows

no code implementations2 Oct 2023 Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Ewa Deelman, Prasanna Balaprakash

To address this problem, we introduce an autoencoder-driven self-supervised learning~(SSL) approach that learns a summary statistic from unlabeled workflow data and estimates the normal behavior of the computational workflow in the latent space.

Anomaly Detection Contrastive Learning +1

Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration

1 code implementation17 Aug 2023 Liyan Wang, Qinyu Yang, Cong Wang, Wei Wang, Jinshan Pan, Zhixun Su

Specifically, our C2F-DFT contains diffusion self-attention (DFSA) and diffusion feed-forward network (DFN) within a new coarse-to-fine training scheme.

Deblurring Image Deblurring +4

Machine Unlearning: Solutions and Challenges

1 code implementation14 Aug 2023 Jie Xu, Zihan Wu, Cong Wang, Xiaohua Jia

Machine learning models may inadvertently memorize sensitive, unauthorized, or malicious data, posing risks of privacy breaches, security vulnerabilities, and performance degradation.

Machine Unlearning

LoLep: Single-View View Synthesis with Locally-Learned Planes and Self-Attention Occlusion Inference

no code implementations ICCV 2023 Cong Wang, Yu-Ping Wang, Dinesh Manocha

We demonstrate the effectiveness of our approach and generate state-of-the-art results on different datasets.

Neural Point-based Volumetric Avatar: Surface-guided Neural Points for Efficient and Photorealistic Volumetric Head Avatar

no code implementations11 Jul 2023 Cong Wang, Di Kang, Yan-Pei Cao, Linchao Bao, Ying Shan, Song-Hai Zhang

Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications.

Intellectual Property Protection of Diffusion Models via the Watermark Diffusion Process

1 code implementation6 Jun 2023 Sen Peng, Yufei Chen, Cong Wang, Xiaohua Jia

This paper introduces WDM, a novel watermarking solution for diffusion models without imprinting the watermark during task generation.

IMAP: Intrinsically Motivated Adversarial Policy

no code implementations4 May 2023 Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang, Chao Shen, Cong Wang

Our experiments validate the effectiveness of the four types of adversarial intrinsic regularizers and BR in enhancing black-box adversarial policy learning across a variety of environments.

Reinforcement Learning (RL)

Unsupervised Multi-Criteria Adversarial Detection in Deep Image Retrieval

no code implementations9 Apr 2023 Yanru Xiao, Cong Wang, Xing Gao

The vulnerability in the algorithm supply chain of deep learning has imposed new challenges to image retrieval systems in the downstream.

Deep Hashing Denoising +2

PeakNet: An Autonomous Bragg Peak Finder with Deep Neural Networks

no code implementations24 Mar 2023 Cong Wang, Po-Nan Li, Jana Thayer, Chun Hong Yoon

PeakNet is well-suited for expert-level real-time serial crystallography data analysis at high data rates.

Semantic Segmentation

SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency

1 code implementation13 Mar 2023 Cong Wang, Jinshan Pan, WanYu Lin, Jiangxin Dong, Xiao-Ming Wu

For this purpose, we develop a prompt based on the features of depth differences between the hazy input images and corresponding clear counterparts that can guide dehazing models for better restoration.

Image Dehazing Image Generation

Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning

1 code implementation1 Mar 2023 Cong Wang, Zhiwei Jiang, Yafeng Yin, Zifeng Cheng, Shiping Ge, Qing Gu

For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.

Ordinal Classification

SpeckleNN: A unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

no code implementations14 Feb 2023 Cong Wang, Eric Florin, Hsing-Yin Chang, Jana Thayer, Chun Hong Yoon

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature.

Classification

Forecasting subcritical cylinder wakes with Fourier Neural Operators

no code implementations19 Jan 2023 Peter I Renn, Cong Wang, Sahin Lale, Zongyi Li, Anima Anandkumar, Morteza Gharib

The learned FNO solution operator can be evaluated in milliseconds, potentially enabling faster-than-real-time modeling for predictive flow control in physical systems.

Operator learning

CIM: Constrained Intrinsic Motivation for Sparse-Reward Continuous Control

no code implementations28 Nov 2022 Xiang Zheng, Xingjun Ma, Cong Wang

Intrinsic motivation is a promising exploration technique for solving reinforcement learning tasks with sparse or absent extrinsic rewards.

Continuous Control Efficient Exploration

Feedback Chain Network For Hippocampus Segmentation

no code implementations15 Nov 2022 Heyu Huang, Runmin Cong, Lianhe Yang, Ling Du, Cong Wang, Sam Kwong

The feedback chain structure unit learns deeper and wider feature representation of each encoder layer through the hierarchical feature aggregation feedback chains, and achieves feature selection and feedback through the feature handover attention module.

feature selection Hippocampus +4

Amplifying Membership Exposure via Data Poisoning

1 code implementation1 Nov 2022 Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang

In this paper, we investigate the third type of exploitation of data poisoning - increasing the risks of privacy leakage of benign training samples.

Data Poisoning Overall - Test +1

Convolutional Embedding Makes Hierarchical Vision Transformer Stronger

no code implementations27 Jul 2022 Cong Wang, Hongmin Xu, Xiong Zhang, Li Wang, Zhitong Zheng, Haifeng Liu

Vision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias.

Inductive Bias

BCS-Net: Boundary, Context and Semantic for Automatic COVID-19 Lung Infection Segmentation from CT Images

3 code implementations17 Jul 2022 Runmin Cong, Haowei Yang, Qiuping Jiang, Wei Gao, Haisheng Li, Cong Wang, Yao Zhao, Sam Kwong

The spread of COVID-19 has brought a huge disaster to the world, and the automatic segmentation of infection regions can help doctors to make diagnosis quickly and reduce workload.

Segmentation

Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement

no code implementations16 Jul 2022 Cong Wang, Jinshan Pan, Xiao-Ming Wu

The generator is based on a U-shaped Transformer which is used to explore non-local information for better clear image restoration.

Image Restoration Low-Light Image Enhancement

Variational Distillation for Multi-View Learning

3 code implementations20 Jun 2022 Xudong Tian, Zhizhong Zhang, Cong Wang, Wensheng Zhang, Yanyun Qu, Lizhuang Ma, Zongze Wu, Yuan Xie, DaCheng Tao

Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions.

MULTI-VIEW LEARNING Representation Learning

Towards Robust 3D Object Recognition with Dense-to-Sparse Deep Domain Adaptation

no code implementations7 May 2022 Prajval Kumar Murali, Cong Wang, Ravinder Dahiya, Mohsen Kaboli

Three-dimensional (3D) object recognition is crucial for intelligent autonomous agents such as autonomous vehicles and robots alike to operate effectively in unstructured environments.

3D Object Recognition Autonomous Vehicles +2

Learning to Classify Open Intent via Soft Labeling and Manifold Mixup

1 code implementation16 Apr 2022 Zifeng Cheng, Zhiwei Jiang, Yafeng Yin, Cong Wang, Qing Gu

In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.

intent-classification Intent Classification +1

Fault Detection and Isolation of Uncertain Nonlinear Parabolic PDE Systems

no code implementations29 Mar 2022 Jingting Zhang, Chengzhi Yuan, Wei Zeng, Cong Wang

This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics.

Decision Making Fault Detection

The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining

no code implementations14 Mar 2022 Yi Liu, Lei Xu, Xingliang Yuan, Cong Wang, Bo Li

Existing machine unlearning techniques focus on centralized training, where access to all holders' training data is a must for the server to conduct the unlearning process.

Federated Learning Machine Unlearning

Load-Flow Solvability under Security Constraints in DC Distribution Networks

no code implementations7 Mar 2022 Zhe Chen, Cong Wang

We present sufficient conditions for the load-flow solvability under security constraints in DC distribution networks.

A Transferable Legged Mobile Manipulation Framework Based on Disturbance Predictive Control

no code implementations2 Mar 2022 Qingfeng Yao, Jilong Wan, Shuyu Yang, Cong Wang, Linghan Meng, Qifeng Zhang, Donglin Wang

Due to their ability to adapt to different terrains, quadruped robots have drawn much attention in the research field of robot learning.

Online-updated High-order Collaborative Networks for Single Image Deraining

no code implementations14 Feb 2022 Cong Wang, Jinshan Pan, Xiao-Ming Wu

Most of the existing deep-learning-based methods constrain the network to generate derained images but few of them explore features from intermediate layers, different levels, and different modules which are beneficial for rain streaks removal.

Single Image Deraining Vocal Bursts Intensity Prediction

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

no code implementations4 Feb 2022 Yifeng Zheng, Shangqi Lai, Yi Liu, Xingliang Yuan, Xun Yi, Cong Wang

In this paper, we present a system design which offers efficient protection of individual model updates throughout the learning procedure, allowing clients to only provide obscured model updates while a cloud server can still perform the aggregation.

Federated Learning

ED2: Environment Dynamics Decomposition World Models for Continuous Control

1 code implementation6 Dec 2021 Jianye Hao, Yifu Yuan, Cong Wang, Zhen Wang

Model-based reinforcement learning (MBRL) achieves significant sample efficiency in practice in comparison to model-free RL, but its performance is often limited by the existence of model prediction error.

Continuous Control Model-based Reinforcement Learning

On the complexity of Dark Chinese Chess

no code implementations6 Dec 2021 Cong Wang, Tongwei Lu

This paper provides a complexity analysis for the game of dark Chinese chess (a. k. a.

Card Games Decision Making

TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion

1 code implementation4 Dec 2021 Yiheng Sun, Tian Lu, Cong Wang, Yuan Li, Huaiyu Fu, Jingran Dong, Yunjie Xu

The prosperity of mobile and financial technologies has bred and expanded various kinds of financial products to a broader scope of people, which contributes to advocating financial inclusion.

Transfer Learning

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

Influence of Binomial Crossover on Approximation Error of Evolutionary Algorithms

no code implementations29 Sep 2021 Cong Wang, Jun He, Yu Chen, Xiufen Zou

Although differential evolution (DE) algorithms perform well on a large variety of complicated optimization problems, only a few theoretical studies are focused on the working principle of DE algorithms.

Evolutionary Algorithms

MotionHint: Self-Supervised Monocular Visual Odometry with Motion Constraints

1 code implementation14 Sep 2021 Cong Wang, Yu-Ping Wang, Dinesh Manocha

A key aspect of our approach is to use an appropriate motion model that can help existing self-supervised monocular VO (SSM-VO) algorithms to overcome issues related to the local minima within their self-supervised loss functions.

Monocular Visual Odometry

Fully Non-Homogeneous Atmospheric Scattering Modeling with Convolutional Neural Networks for Single Image Dehazing

no code implementations25 Aug 2021 Cong Wang, Yan Huang, Yuexian Zou, Yong Xu

However, it is noted that ASM-based SIDM degrades its performance in dehazing real world hazy images due to the limited modelling ability of ASM where the atmospheric light factor (ALF) and the angular scattering coefficient (ASC) are assumed as constants for one image.

Image Dehazing Single Image Dehazing

TDLS: A Top-Down Layer Searching Algorithm for Generating Counterfactual Visual Explanation

no code implementations8 Aug 2021 Cong Wang, Haocheng Han, Caleb Chen Cao

Explanation of AI, as well as fairness of algorithms' decisions and the transparency of the decision model, are becoming more and more important.

counterfactual Counterfactual Explanation +2

Teacher Model Fingerprinting Attacks Against Transfer Learning

2 code implementations23 Jun 2021 Yufei Chen, Chao Shen, Cong Wang, Yang Zhang

To this end, we propose a teacher model fingerprinting attack to infer the origin of a student model, i. e., the teacher model it transfers from.

Transfer Learning

You See What I Want You To See: Exploring Targeted Black-Box Transferability Attack for Hash-Based Image Retrieval Systems

no code implementations CVPR 2021 Yanru Xiao, Cong Wang

In this paper, we start from an adversarial standpoint to explore and enhance the capacity of targeted black-box transferability attack for deep hashing.

Deep Hashing Image Retrieval

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

FWB-Net:Front White Balance Network for Color Shift Correction in Single Image Dehazing via Atmospheric Light Estimation

no code implementations21 Jan 2021 Cong Wang, Yan Huang, Yuexian Zou, Yong Xu

However, for images taken in real-world, the illumination is not uniformly distributed over whole image which brings model mismatch and possibly results in color shift of the deep models using ASM.

Image Dehazing Single Image Dehazing

Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses

no code implementations8 Dec 2020 Yi Liu, Xingliang Yuan, Ruihui Zhao, Cong Wang, Dusit Niyato, Yefeng Zheng

Extensive case studies have shown that our attacks are effective on different datasets and common semi-supervised learning methods.

Federated Learning Quantization

Logical peering for interdomain networking on testbeds

1 code implementation9 Oct 2020 Yuanjun Yao, Qiang Cao, Paul Ruth, Mert Cevik, Cong Wang, Jeff Chase

Research testbed fabrics have potential to support long-lived, evolving, interdomain experiments, including opt-in application traffic across multiple campuses and edge sites.

Networking and Internet Architecture

Joint Self-Attention and Scale-Aggregation for Self-Calibrated Deraining Network

1 code implementation6 Aug 2020 Cong Wang, Yutong Wu, Zhixun Su, Junyang Chen

In the field of multimedia, single image deraining is a basic pre-processing work, which can greatly improve the visual effect of subsequent high-level tasks in rainy conditions.

Single Image Deraining

DCSFN: Deep Cross-scale Fusion Network for Single Image Rain Removal

no code implementations3 Aug 2020 Cong Wang, Xiaoying Xing, Zhixun Su, Junyang Chen

Further, we design an inner-scale connection block to utilize the multi-scale information and features fusion way between different scales to improve rain representation ability and we introduce the dense block with skip connection to inner-connect these blocks.

Rain Removal

A Framework for Behavioral Biometric Authentication using Deep Metric Learning on Mobile Devices

no code implementations26 May 2020 Cong Wang, Yanru Xiao, Xing Gao, Li Li, Jun Wang

We show the feasibility of training with mobile CPUs, where training 100 epochs takes less than 10 mins and can be boosted 3-5 times with feature transfer.

Metric Learning Multi-class Classification

Towards Efficient Scheduling of Federated Mobile Devices under Computational and Statistical Heterogeneity

no code implementations25 May 2020 Cong Wang, Yuanyuan Yang, Pengzhan Zhou

While the current research mainly focuses on optimizing learning algorithms and minimizing communication overhead left by distributed learning, there is still a considerable gap when it comes to the real implementation on mobile devices.

Federated Learning Scheduling

Residual-driven Fuzzy C-Means Clustering for Image Segmentation

no code implementations15 Apr 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou

Due to its inferior characteristics, an observed (noisy) image's direct use gives rise to poor segmentation results.

Clustering Image Segmentation +2

Physical Model Guided Deep Image Deraining

no code implementations30 Mar 2020 Honghe Zhu, Cong Wang, Ya-Jie Zhang, Zhixun Su, Guohui Zhao

Single image deraining is an urgent task because the degraded rainy image makes many computer vision systems fail to work, such as video surveillance and autonomous driving.

Autonomous Driving Single Image Deraining

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection

1 code implementation11 Mar 2020 Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu

Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection.

Dimensionality Reduction Fraud Detection +2

Kullback-Leibler Divergence-Based Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation

no code implementations21 Feb 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou

Considering these feature sets as data of clustering, an modified FCM algorithm is proposed, which introduces a KL divergence term in the partition matrix into its objective function.

Clustering Image Segmentation +2

Residual-Sparse Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet frames

no code implementations14 Feb 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou, Jun Zhao

To further enhance the segmentation effects of the improved FCM algorithm, we also employ the morphological reconstruction to smoothen the labels generated by clustering.

Clustering Image Segmentation +1

Error Analysis of Elitist Randomized Search Heuristics

no code implementations3 Sep 2019 Cong Wang, Yu Chen, Jun He, Chengwang Xie

When globally optimal solutions of complicated optimization problems cannot be located by evolutionary algorithms (EAs) in polynomial expected running time, the hitting time/running time analysis is not flexible enough to accommodate the requirement of theoretical study, because sometimes we have no idea on what approximation ratio is available in polynomial expected running time.

Evolutionary Algorithms

Defeating Misclassification Attacks Against Transfer Learning

no code implementations29 Aug 2019 Bang Wu, Shuo Wang, Xingliang Yuan, Cong Wang, Carsten Rudolph, Xiangwen Yang

To avoid the bloated ensemble size during inference, we propose a two-phase defence, in which inference from the Student model is firstly performed to narrow down the candidate differentiators to be assembled, and later only a small, fixed number of them can be chosen to validate clean or reject adversarial inputs effectively.

Network Pruning Transfer Learning

Hierarchical Clustering Supported by Reciprocal Nearest Neighbors

no code implementations9 Jul 2019 Wen-Bo Xie, Yan-Li Lee, Cong Wang, Duan-Bing Chen, Tao Zhou

Clustering is a fundamental analysis tool aiming at classifying data points into groups based on their similarity or distance.

Astronomy Clustering +1

Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality

no code implementations17 Feb 2019 Guang-Yu Nie, Yun Liu, Cong Wang, Yue Liu, Yongtian Wang

Three-dimensional (3-D) scene reconstruction is one of the key techniques in Augmented Reality (AR), which is related to the integration of image processing and display systems of complex information.

Stereo Matching Stereo Matching Hand

Identifying the Mislabeled Training Samples of ECG Signals using Machine Learning

no code implementations11 Dec 2017 Yaoguang Li, Wei Cui, Cong Wang

The classification accuracy of electrocardiogram signal is often affected by diverse factors in which mislabeled training samples issue is one of the most influential problems.

BIG-bench Machine Learning Classification +1

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