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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：213/54  |  提交时间：2023/02/22
Global instance tracking  single object tracking  benchmark dataset  performance evaluation  human tracking ability  
Temporal-adaptive sparse feature aggregation for video object detection 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 127, 页码: 108587
作者:  He, Fei;  Li, Qiaozhe;  Zhao, Xin;  Huang, Kaiqi
Adobe PDF(1549Kb)  |  收藏  |  浏览/下载：292/38  |  提交时间：2022/06/10
Video object detection  Temporal-adaptive sparse sampling  Pixel-adaptive aggregation  Object-relational aggregation  
AHDet: A dynamic coarse-to-fine gaze strategy for active object detection 期刊论文
NEUROCOMPUTING, 2022, 卷号: 491, 页码: 522-532
作者:  Xu, Nuo;  Huo, Chunlei;  Zhang, Xin;  Pan, Chunhong
Adobe PDF(2664Kb)  |  收藏  |  浏览/下载：285/57  |  提交时间：2022/09/19
Object detection  Active object detection  Deep reinforcement learning  Convolutional neural networks  
Heterogeneous Relational Graph Neural Networks with Adaptive Objective for End-to-End Task-Oriented Dialogue 期刊论文
KNOWLEDGE-BASED SYSTEMS, 2021, 卷号: 227, 期号: 2021, 页码: 107186
作者:  Liu, Qingbin;  Bai, Guirong;  He, Shizhu;  Liu, Cao;  Liu, Kang;  Zhao, Jun
Adobe PDF(1021Kb)  |  收藏  |  浏览/下载：288/58  |  提交时间：2021/11/02
End-to-end task-oriented dialogue  Heterogeneous relational graph neural networks  Shared-private parameterization  Hierarchical attention mechanism  Adaptive objective  
Robot learning through observation via coarse-to-fine grained video summarization 期刊论文
APPLIED SOFT COMPUTING, 2021, 卷号: 99, 期号: /, 页码: 106913
作者:  Zhang, Yujia;  Li, Qianzhong;  Zhao, Xiaoguang;  Tan, Min
Adobe PDF(5989Kb)  |  收藏  |  浏览/下载：330/68  |  提交时间：2021/03/08
Robotic vision  Learning through observation  Coarse-to-fine video summarization  
Nocal-Siam: Refining Visual Features and Response With Advanced Non-Local Blocks for Real-Time Siamese Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 2656-2668
作者:  Tan, Huibin;  Zhang, Xiang;  Zhang, Zhipeng;  Lan, Long;  Zhang, Wenju;  Luo, Zhigang
Adobe PDF(2898Kb)  |  收藏  |  浏览/下载：160/38  |  提交时间：2021/03/29
Target tracking  Visualization  Feature extraction  Real-time systems  Oceans  Convolution  Task analysis  Siamese trackers  non-local attention  supervisedly attentive  
Changes of Effective Connectivity in the Alpha Band Characterize Differential Processing of Audiovisual Information in Cross-Modal Selective Attention 期刊论文
NEUROSCIENCE BULLETIN, 2020, 卷号: 36, 期号: 9, 页码: 1009-1022
作者:  Niu, Weikun;  Jiang, Yuying;  Zhang, Xin;  Jiang, Tianzi;  Zhang, Yujin;  Yu, Shan
Adobe PDF(3941Kb)  |  收藏  |  浏览/下载：232/0  |  提交时间：2020/08/24
Human EEG  Audiovisual selective attention  Granger Causality  Pattern classification  
Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2020, 卷号: 无, 期号: 无, 页码: 无
作者:  Chen, Xingyu;  Yu, Junzhi;  Kong, Shihan;  Wu, Zhengxing;  Wen, Li
浏览  |  Adobe PDF(4122Kb)  |  收藏  |  浏览/下载：228/55  |  提交时间：2020/06/08
Object detection  Neural networks  Computer vision  Deep learning  
Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences 期刊论文
Medical Image Analysis, 2020, 卷号: 65, 期号: 65, 页码: 101793
作者:  Fei Liu;  Dan Liu;  Jie Tian;  Xiaoyan Xie;  Xin Yang;  Wang K(王坤)
浏览  |  Adobe PDF(3180Kb)  |  收藏  |  浏览/下载：186/54  |  提交时间：2020/11/02
Ultrasound sequence  Respiratory motion estimation  Cascaded Siamese network  One-shot deformable convolution  
Dynamic Collaborative Tracking 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 10, 页码: 3035-3046
作者:  Zhu, Guibo;  Zhang, Zhaoxiang;  Wang, Jinqiao;  Wu, Yi;  Lu, Hanqing
浏览  |  Adobe PDF(2492Kb)  |  收藏  |  浏览/下载：478/144  |  提交时间：2018/10/11
Correlation filter (CF)  distracter suppression  online learning  visual tracking