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Global Instance Tracking: Locating Target More Like Humans 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 1, 页码: 576-592
作者:  Hu, Shiyu;  Zhao, Xin;  Huang, Lianghua;  Huang, Kaiqi
Adobe PDF(15055Kb)  |  收藏  |  浏览/下载：229/54  |  提交时间：2023/02/22
Global instance tracking  single object tracking  benchmark dataset  performance evaluation  human tracking ability  
Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk 期刊论文
TRANSLATIONAL LUNG CANCER RESEARCH, 2022, 页码: 23
作者:  He, Bing-Xi;  Zhong, Yi-Fan;  Zhu, Yong-Bei;  Deng, Jia-Jun;  Fang, Meng-Jie;  She, Yun-Lang;  Wang, Ting-Ting;  Yang, Yang;  Sun, Xi-Wen;  Belluomini, Lorenzo;  Watanabe, Satoshi;  Dong, Di;  Tian, Jie;  Xie, Dong
Adobe PDF(3742Kb)  |  收藏  |  浏览/下载：334/40  |  提交时间：2022/06/10
Tumor biomarkers  immunotherapy  lung neoplasms  programmed cell death 1 receptor (PD-1 receptor)  biostatistics  
Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma 期刊论文
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 页码: 11
作者:  Zhao, Xun;  Liang, Yu-Jing;  Zhang, Xu;  Wen, Dong-Xiang;  Fan, Wei;  Tang, Lin-Quan;  Dong, Di;  Tian, Jie;  Mai, Hai-Qiang
Adobe PDF(1720Kb)  |  收藏  |  浏览/下载：325/46  |  提交时间：2022/06/10
Recurrent nasopharyngeal carcinoma  Survival analysis  Radiomics  Deep learning  
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
Adobe PDF(4187Kb)  |  收藏  |  浏览/下载：219/1  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)