中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共12条，第1-10条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
EDP: An Efficient Decomposition and Pruning Scheme for Convolutional Neural Network Compression 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 32, 期号: 0, 页码: 0
作者:  Ruan, Xiaofeng;  Liu, Yufan;  Yuan, Chunfeng;  Li, Bing;  Hu, Weiming;  Li, Yangxi;  Maybank, Stephen
Adobe PDF(3625Kb)  |  收藏  |  浏览/下载：303/43  |  提交时间：2021/06/17
Data-driven  low-rank decomposition  model compression and acceleration  structured pruning  
Adaptive super -resolution for person re-identification with low-resolution images 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 114, 页码: 107682
作者:  Han, Ke;  Huang, Yan;  Song, Chunfeng;  Wang, Liang;  Tan, Tieniu
Adobe PDF(2944Kb)  |  收藏  |  浏览/下载：333/37  |  提交时间：2021/05/06
Person re-identification  Super-resolution  Body regions  Adaptive feature integration  
Knowledge-driven Egocentric Multimodal Activity Recognition 期刊论文
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2020, 卷号: 16, 期号: 4, 页码: 21
作者:  Huang, Yi;  Yang, Xiaoshan;  Gao, Junyu;  Sang, Jitao;  Xu, Changsheng
Adobe PDF(1875Kb)  |  收藏  |  浏览/下载：372/50  |  提交时间：2021/03/08
Egocentric videos  wearable sensors  graph neural networks  
High-speed rail pole number recognition through deep representation and temporal redundancy 期刊论文
NEUROCOMPUTING, 2020, 卷号: 415, 页码: 201-214
作者:  Yang, Yang;  Zhang, Wensheng;  He, Zewen;  Li, Ding
Adobe PDF(2751Kb)  |  收藏  |  浏览/下载：295/54  |  提交时间：2021/01/07
Region-based convolutional neural network  Context information  Object detection  Number recognition  Pole number  High-speed rail  
Investigating the dynamic memory effect of human drivers via ON-LSTM 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 卷号: 63, 期号: 9, 页码: 11
作者:  Dai, Shengzhe;  Li, Zhiheng;  Li, Li;  Cao, Dongpu;  Dai, Xingyuan;  Lin, Yilun
Adobe PDF(325Kb)  |  收藏  |  浏览/下载：273/52  |  提交时间：2020/12/04
driving behavior  memory effect  trajectory prediction  historical information  ON-LSTM  
CADN: A weakly supervised learning-based category-aware object detection network for surface defect detection 期刊论文
Pattern Recognition, 2020, 卷号: 109, 期号: 0, 页码: 10
作者:  Zou W(邹伟)
浏览  |  Adobe PDF(1839Kb)  |  收藏  |  浏览/下载：165/49  |  提交时间：2020/10/22
Weakly supervised learning, Automated surface inspection, Defect detection, Knowledge distillation  
Improve Person Re-Identification With Part Awareness Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7468-7481
作者:  Huang, Houjing;  Yang, Wenjie;  Lin, Jinbin;  Huang, Guan;  Xu, Jiamiao;  Wang, Guoli;  Chen, Xiaotang;  Huang, Kaiqi
Adobe PDF(3927Kb)  |  收藏  |  浏览/下载：319/56  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Visual Defect Inspection for Deep-Aperture Components With Coarse-to-Fine Contour Extraction 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 卷号: 69, 期号: 6, 页码: 3262-3274
作者:  Gong, Xinyi;  Su, Hu;  Xu, De;  Zhang, Jiabin;  Zhang, Lei;  Zhang, Zhengtao
浏览  |  Adobe PDF(1324Kb)  |  收藏  |  浏览/下载：342/73  |  提交时间：2020/08/03
Coarse-fine positioning  deep-hole component  defect inspection  edge grouping  image processing  
Deep learning -based multi -view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 128, 期号: 109041, 页码: 9
作者:  Wu, Xiangjun;  Hui, Hui;  Niu, Meng;  Li, Liang;  Wang, Li;  He, Bingxi;  Yang, Xin;  Li, Li;  Li, Hongjun;  Tian, Jie;  Zha, Yunfei
浏览  |  Adobe PDF(2315Kb)  |  收藏  |  浏览/下载：346/65  |  提交时间：2020/07/20
Coronavirus disease 2019  Deep learning  Multi-view model  Computed tomography  
Deep learning -based multi -view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 128, 期号: 109041, 页码: 9
作者:  Wu, Xiangjun;  Hui, Hui;  Niu, Meng;  Li, Liang;  Wang, Li;  He, Bingxi;  Yang, Xin;  Li, Li;  Li, Hongjun;  Tian, Jie;  Zha, Yunfei
浏览  |  Adobe PDF(2315Kb)  |  收藏  |  浏览/下载：307/47  |  提交时间：2020/07/20
Coronavirus disease 2019  Deep learning  Multi-view model  Computed tomography