CASIA OpenIR

浏览/检索结果: 共19条,第1-10条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Pose Measurement of Large Cabin Based on Point Cloud in Multi-robot Assembly 会议论文
, Shanghai, China, 2020-11
作者:  Wang, Zhe;  Liu, Zhaoyang;  Fan, Junfeng;  Jing, Fengshui
Adobe PDF(1315Kb)  |  收藏  |  浏览/下载:228/52  |  提交时间:2021/06/22
Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI 会议论文
, Lima, 2020/10/4
作者:  Dongren Yao;  Jing Sui;  Erkun Yang;  Pew-Thian Yap;  Dinggang Shen;  Mingxia Liu
Adobe PDF(796Kb)  |  收藏  |  浏览/下载:174/54  |  提交时间:2021/06/18
Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search 会议论文
, New York, USA, 2020-2
作者:  Jing Y(荆雅);  Si CY(司晨阳);  Wang JB(王君波);  Wang W(王威);  Wang L(王亮);  Tan TN(谭铁牛)
Adobe PDF(4627Kb)  |  收藏  |  浏览/下载:198/49  |  提交时间:2021/06/07
Non-Negative Iterative Convex Refinement Approach for Accurate and Robust Reconstruction in Cerenkov Luminescence Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 卷号: 39, 期号: 10, 页码: 3207-3217
作者:  Cai, Meishan;  Zhang, Zeyu;  Shi, Xiaojing;  Yang, Junying;  Hu, Zhenhua;  Tian, Jie
Adobe PDF(2176Kb)  |  收藏  |  浏览/下载:363/76  |  提交时间:2021/01/07
Image reconstruction  Imaging  Mathematical model  Shape  Slabs  Iterative methods  Luminescence  Cerenkov luminescence tomography  sparse reconstruction  inverse problem  tumor  
Multi-task autoencoder based classification-regression model for patient-specific VMAT QA 期刊论文
PHYSICS IN MEDICINE AND BIOLOGY, 2020, 卷号: 65, 期号: 23, 页码: 12
作者:  Wang, Le;  Li, Jiaqi;  Zhang, Shuming;  Zhang, Xile;  Zhang, Qilin;  Chan, Maria F.;  Yang, Ruijie;  Sui, Jing
Adobe PDF(926Kb)  |  收藏  |  浏览/下载:468/98  |  提交时间:2021/01/06
VMAT QA  patient-specific QA  deep learning  radiotherapy  
Nanobar array assay revealed complementary roles of BIN1 splice isoforms in cardiac T-tubule morphogenesis 期刊论文
Nano Letters, 2020, 卷号: 20, 期号: 20, 页码: 9
作者:  Lin-Lin Li;  Qian-Jin Guo;  Hsin-Ya Lou;  Jing-Hui Liang;  Yang Yang;  Xin Xing;  Hong-Tao Li;  Jing Han;  Shan Shen;  Hui Li;  Haihong Ye;  Hao Di Wu;  Bianxiao Cui;  Shi-Qiang Wang
浏览  |  Adobe PDF(7678Kb)  |  收藏  |  浏览/下载:270/56  |  提交时间:2020/10/14
nanopillar array BIN1 splicing isoforms T-tubule muscle contraction heart disease  
Radiomics Based on MRI as a Biomarker to Guide Therapy by Predicting Upgrading of Prostate Cancer From Biopsy to Radical Prostatectomy 期刊论文
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2020, 页码: 10
作者:  Zhang, Gu-mu-yang;  Han, Yu-qi;  Wei, Jing-wei;  Qi, Ya-fei;  Gu, Dong-sheng;  Lei, Jing;  Yan, Wei-gang;  Xiao, Yu;  Xue, Hua-dan;  Feng, Feng;  Sun, Hao;  Jin, Zheng-yu;  Tian, Jie
收藏  |  浏览/下载:304/0  |  提交时间:2020/09/28
radiomics  magnetic resonance imaging  prostate cancer  Gleason score  
Automatic Reconstruction of Mitochondria and Endoplasmic Reticulum in Electron Microscopy Volumes by Deep Learning 期刊论文
FRONTIERS IN NEUROSCIENCE, 2020, 期号: 14, 页码: 13
作者:  Liu, Jing;  Li, Linlin;  Yang, Yang;  Hong, Bei;  Chen, Xi;  Xie, Qiwei;  Han, Hua
浏览  |  Adobe PDF(1944Kb)  |  收藏  |  浏览/下载:330/77  |  提交时间:2020/09/21
mitochondria  endoplasmic reticulum  electron microscopes  segmentation  3D reconstruction  
NR4A1 Methylation Associated Multimodal Neuroimaging Patterns Impaired in Temporal Lobe Epilepsy 期刊论文
FRONTIERS IN NEUROSCIENCE, 2020, 卷号: 14, 期号: 727, 页码: 10
作者:  Zhi, Dongmei;  Wu, Wenyue;  Xiao, Bo;  Qi, Shile;  Jiang, Rongtao;  Yang, Xingdong;  Yang, Jian;  Xiao, Wenbiao;  Liu, Chaorong;  Long, Hongyu;  Calhoun, Vince D.;  Long, Lili;  Sui, Jing
Adobe PDF(13713Kb)  |  收藏  |  浏览/下载:367/57  |  提交时间:2020/09/07
temporal lobe epilepsy  multimodal fusion  functional connectivity  fractional anisotropy  gray matter volume  
Skeleton-based action recognition with hierarchical spatial reasoning and temporal stack learning network 期刊论文
PATTERN RECOGNITION, 2020, 卷号: 107, 期号: 107511, 页码: 12
作者:  Si, Chenyang;  Jing, Ya;  Wang, Wei;  Wang, Liang;  Tan, Tieniu
Adobe PDF(2378Kb)  |  收藏  |  浏览/下载:391/74  |  提交时间:2020/08/31
Skeleton-based action recognition  Hierarchical spatial reasoning  Temporal stack learning  Clip-based incremental loss