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浏览/检索结果: 共78条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Few-shot video object segmentation with prototype evolution 期刊论文  OAI收割 NEURAL COMPUTING & APPLICATIONS, 2024, 页码: 16 作者:  Mao, Binjie;  Liu, Xiyan;  Shi, Linsu;  Yu, Jiazhong;  Li, Fei   |  收藏  |  浏览/下载：4/0  |  提交时间：2024/02/21 Few-shot video segmentation  Few-shot segmentation  Video object segmentation   Coarse-to-Fine Video Instance Segmentation With Factorized Conditional Appearance Flows 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 5, 页码: 1192-1208 作者:  Zheyun Qin;  Xiankai Lu;  Xiushan Nie;  Dongfang Liu;  Yilong Yin   |  收藏  |  浏览/下载：4/0  |  提交时间：2023/04/26 Embedding learning  generative model  normalizing flows  video instance segmentation (VIS)   InsPro: Propagating Instance Query and Proposal for Online Video Instance Segmentation 会议论文  OAI收割 New Orleans, 2022-11 作者:  He, Fei;  Zhang, Haoyang;  Gao, Naiyu;  Jia, Jian;  Shan, Yanhu   |  收藏  |  浏览/下载：11/0  |  提交时间：2023/06/09 Scribble-Supervised Video Object Segmentation 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 2, 页码: 339-353 作者:  Peiliang Huang;  Junwei Han;  Nian Liu;  Jun Ren;  Dingwen Zhang   |  收藏  |  浏览/下载：50/0  |  提交时间：2021/11/03 Convolutional neural networks (CNNs)  scribble  self-attention  video object segmentation  weakly supervised   Public Opinions and Concerns Regarding the Canadian Prime Minister's Daily COVID-19 Briefing: Longitudinal Study of YouTube Comments Using Machine Learning Techniques 期刊论文  OAI收割 JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 卷号: 23, 期号: 2, 页码: 12 作者:  Zheng, Chengda;  Xue, Jia;  Sun, Yumin;  Zhu, Tingshao   |  收藏  |  浏览/下载：21/0  |  提交时间：2021/04/19 Canada  PM Trudeau  YouTube  machine learning  big data  infodemiology  infodemic  public concerns  communication  concern  social media  video   Directional Deep Embedding and Appearance Learning for Fast Video Object Segmentation 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11 作者:  Yin, Yingjie;  Xu, De;  Wang, Xingang;  Zhang, Lei   |  收藏  |  浏览/下载：10/0  |  提交时间：2022/02/16 Feature extraction  Kernel  Object segmentation  Faces  Probabilistic logic  Learning systems  Image segmentation  Deep appearance learning  directional deep embedding learning  directional statistics-based learning  video object segmentation (VOS)   Metadata Connector: Exploiting Hashtag and Tag for Cross-OSN Event Search 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 510-523 作者:  Gao, Yuqi;  Sang, Jitao;  Fu, Chengpeng;  Wang, Zhengjia;  Ren, Tongwei   |  收藏  |  浏览/下载：53/0  |  提交时间：2021/03/08 Twitter  Tagging  Videos  YouTube  Flickr  Games  Social media search  cross-OSN application  social multimedia   Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information Networks 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 卷号: 23, 页码: 2019-2032 作者:  Sang, Lei;  Xu, Min;  Qian, Shengsheng;  Martin, Matt;  Li, Peter   |  收藏  |  浏览/下载：24/0  |  提交时间：2021/08/15 Semantics  Collaboration  YouTube  Australia  Visualization  Context modeling  Video recommendation  context-dependent propagating  Heterogeneous Information Network (HIN)  Network embedding   Property-Constrained Dual Learning for Video Summarization 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 3989-4000 作者:  Zhao, Bin;  Li, Xuelong;  Lu, Xiaoqiang   |  收藏  |  浏览/下载：25/0  |  提交时间：2020/11/02 Generators  Task analysis  Recurrent neural networks  Machine learning  Training  Semantics  Learning systems  Dual learning  property model  recurrent neural network (RNN)  video summarization   Brain-Inspired Active Learning Architecture for Procedural Knowledge Understanding Based on Human-Robot Interaction 期刊论文  OAI收割 COGNITIVE COMPUTATION, 2020, 页码: 13 作者:  Zhang, Tielin;  Zeng, Yi;  Pan, Ruihan;  Shi, Mengting;  Lu, Enmeng   |  收藏  |  浏览/下载：18/0  |  提交时间：2020/08/24 Brain-inspired architecture  Procedural knowledge  Deep neural network  Reinforcement learning  Knowledge graph