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A Task-Adaptive In-Situ ReRAM Computing for Graph Convolutional Networks 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2024, 卷号: 43, 期号: 9, 页码: 2635-2646
作者:  He, Yintao;  Li, Bing;  Wang, Ying;  Liu, Cheng;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载:2/0  |  提交时间:2024/12/06
Task analysis  Sparse matrices  Convolution  Convolutional neural networks  Design automation  Neural networks  Integrated circuits  Graph convolutional network  hardware acceleration  processing-in-memory  
Exploring Winograd Convolution for Cost-Effective Neural Network Fault Tolerance 期刊论文
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2023, 卷号: 31, 期号: 11, 页码: 1763-1773
作者:  Xue, Xinghua;  Liu, Cheng;  Liu, Bo;  Huang, Haitong;  Wang, Ying;  Luo, Tao;  Zhang, Lei;  Li, Huawei;  Li, Xiaowei
收藏  |  浏览/下载:11/0  |  提交时间:2024/05/20
Fault tolerant systems  Fault tolerance  Artificial neural networks  Convolution  Reliability  Computational modeling  Neurons  Fault-tolerance  soft errors  vulnerability analysis  winograd convolution (WG-Conv)  
Search-Free Inference Acceleration for Sparse Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2022, 卷号: 41, 期号: 7, 页码: 2156-2169
作者:  Liu, Bosheng;  Chen, Xiaoming;  Han, Yinhe;  Wu, Jigang;  Chang, Liang;  Liu, Peng;  Xu, Haobo
收藏  |  浏览/下载:32/0  |  提交时间:2022/12/07
Internal interconnection  memory bandwidth  sparse accelerators  sparse convolution neural networks (CNNs)  
A Decomposable Winograd Method for N-D Convolution Acceleration in Video Analysis 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2021, 页码: 21
作者:  Huang, Di;  Zhang, Rui;  Zhang, Xishan;  Wu, Fan;  Wang, Xianzhuo;  Jin, Pengwei;  Liu, Shaoli;  Li, Ling;  Chen, Yunji
收藏  |  浏览/下载:45/0  |  提交时间:2021/12/01
Convolution neural networks  Model acceleration  Winograd algorithm  Video analysis  
Hybrid-Attention Enhanced Two-Stream Fusion Network for Video Venue Prediction 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2917-2929
作者:  Zhang, Yanchao;  Min, Weiqing;  Nie, Liqiang;  Jiang, Shuqiang
收藏  |  浏览/下载:46/0  |  提交时间:2021/12/01
Visualization  Feature extraction  Convolution  Streaming media  Object oriented modeling  Three-dimensional displays  Neural networks  Feature extraction  knowledge representation  supervised learning  video signal processing  
Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks 期刊论文
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2020, 卷号: 92, 期号: 3, 页码: 325-333
作者:  Liu, Xiuling;  Du, Jiaxing;  Yang, Jianli;  Xiong, Peng;  Liu, Jing;  Lin, Feng
收藏  |  浏览/下载:57/0  |  提交时间:2020/12/10
Coronary heart disease  Fibrous plaque  Optical coherence tomography  Multi-scale convolution neural networks  
Moving Object Detection With Deep CNNs 期刊论文
IEEE ACCESS, 2020, 卷号: 8, 页码: 29729-29741
作者:  Zhu, Haidi;  Yan, Xin;  Tang, Hongying;  Chang, Yuchao;  Li, Baoqing;  Yuan, Xiaobing
收藏  |  浏览/下载:50/0  |  提交时间:2020/12/10
Connected region detection  deep convolution neural networks  foreground extraction  high resolution  moving object detection  
Scene Recognition With Prototype-Agnostic Scene Layout 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 5877-5888
作者:  Chen, Gongwei;  Song, Xinhang;  Zeng, Haitao;  Jiang, Shuqiang
收藏  |  浏览/下载:45/0  |  提交时间:2020/12/10
Layout  Semantics  Prototypes  Image recognition  Convolution  Neural networks  Deformable models  Scene classification  convolution neural networks  graph neural networks  scene layout  
面向稀疏卷积神经网络的GPU性能优化方法 期刊论文
软件学报, 2020, 卷号: 31, 期号: 9, 页码: 2944
作者:  董晓;  刘雷;  李晶;  冯晓兵
收藏  |  浏览/下载:14/0  |  提交时间:2023/12/04
neural networks  sparse  GPU  performance optimization  convolution  code generation  神经网络  稀疏  GPU  性能优化  卷积  代码生成  
CSCC: Convolution Split Compression Calculation Algorithm for Deep Neural Network 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 页码: 71607-71615
作者:  Fan, Shengyu;  Yu, Hui;  Lu, Dianjie;  Jiao, Shuai;  Xu, Weizhi;  Liu, Fangai;  Liu, Zhiyong
收藏  |  浏览/下载:244/0  |  提交时间:2019/08/16
Convolutional neural network  sparse matrix vector multiplication  neural networks  convolution  sparse matrices