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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：313/44  |  提交时间：2021/03/08
Egocentric videos  wearable sensors  graph neural networks  
CI-GNN: Building a Category-Instance Graph for Zero-Shot Video Classification 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 12, 页码: 3088-3100
作者:  Gao, Junyu;  Xu, Changsheng
收藏  |  浏览/下载：142/0  |  提交时间：2021/03/01
Semantics  Task analysis  Visualization  Training  Message passing  Pattern recognition  Neural networks  Zero-shot video classification  graph neural network  zero-shot learning  
Anchor-Free One-Stage Online Multi-Object Tracking 会议论文
, 中国，南京, 2020-10
作者:  Zhou, Zongwei;  Li, Yangxi;  Gao, Jin;  Xing, Junliang;  Li, Liang;  Hu, Weiming
Adobe PDF(634Kb)  |  收藏  |  浏览/下载：202/48  |  提交时间：2021/06/23
Anchor-Free · One-Stage · Multi-Object Tracking  
Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Scale-Dependent Lyapunov Exponent 期刊论文
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2020, 卷号: 8, 页码: 14
作者:  Li, Qiong;  Gao, Jianbo;  Huang, Qi;  Wu, Yuan;  Xu, Bo
收藏  |  浏览/下载：145/0  |  提交时间：2021/01/07
EEG  epileptiform discharges  power spectral density (PSD)  scale-dependent Lyapunov exponent (SDLE)  random forest classifier  support vector machine (SVM)  
Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Adaptive Fractal and Network Analysis: A Clinical Perspective 期刊论文
FRONTIERS IN PHYSIOLOGY, 2020, 卷号: 11, 页码: 15
作者:  Li, Qiong;  Gao, Jianbo;  Zhang, Ziwen;  Huang, Qi;  Wu, Yuan;  Xu, Bo
收藏  |  浏览/下载：138/0  |  提交时间：2020/09/28
EEG  epileptiform discharges  adaptive fractal analysis  Hurst parameter  singular value decomposition  brain network  
Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study 期刊论文
ANNALS OF ONCOLOGY, 2020, 卷号: 31, 期号: 7, 页码: 912-920
作者:  Dong, D.;  Fang, M. -J.;  Tang, L.;  Shan, X. -H.;  Gao, J. -B.;  Giganti, F.;  Wang, R. -P.;  Chen, X.;  Wang, X. -X.;  Palumbo, D.;  Fu, J.;  Li, W. -C.;  Li, J.;  Zhong, L. -Z.;  De Cobelli, F.;  Ji, J. -F.;  Liu, Z. -Y.;  Tian, J.
收藏  |  浏览/下载：236/0  |  提交时间：2020/07/20
Precise visual distinction of brain glioma from normal tissues via targeted photoacoustic and fluorescence navigation 期刊论文
NANOMEDICINE-NANOTECHNOLOGY BIOLOGY AND MEDICINE, 2020, 卷号: 27, 页码: 9
作者:  Jia, Xiaohua;  Fan, Kelong;  Zhang, Ruofei;  Zhang, Dan;  Zhang, Jianjun;  Gao, Yuan;  Zhang, Tao;  Li, Wanjun;  Li, Junlai;  Yan, Xiyun;  Tian, Jie
收藏  |  浏览/下载：184/0  |  提交时间：2020/08/21
Glioma  Molecular imaging  Transferrin receptor 1  Nanoparticles  
Find objects and focus on highlights: Mining object semantics for video highlight detection via graph neural networks 会议论文
, Palo Alto, California USA, 2020-02-07
作者:  Zhang, Yingying;  Gao, Junyu;  Yang, Xiaoshan;  Liu, Chang;  Li, Yan;  Xu, Changsheng
收藏  |  浏览/下载：61/0  |  提交时间：2023/04/25
Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 939-955
作者:  Gao, Jin;  Wang, Qiang;  Xing, Junliang;  Ling, Haibin;  Hu, Weiming;  Maybank, Stephen
收藏  |  浏览/下载：248/0  |  提交时间：2020/06/02
Task analysis  Correlation  Target tracking  Probability distribution  Visualization  Collaboration  Visual tracking  Gaussian processes  correlation filters  transfer learning  tracking-by-fusion  
Deep Self-Evolution Clustering 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 809-823
作者:  Chang, Jianlong;  Meng, Gaofeng;  Wang, Lingfeng;  Xiang, Shiming;  Pan, Chunhong
浏览  |  Adobe PDF(4817Kb)  |  收藏  |  浏览/下载：380/85  |  提交时间：2020/06/02
Task analysis  Unsupervised learning  Training  Clustering methods  Pattern analysis  Clustering  deep self-evolution clustering  self-evolution clustering training  deep unsupervised learning