CSpace

浏览/检索结果: 共6条,第1-6条 帮助

已选(0)清除 条数/页:   排序方式:
Robust Spatial Matching for Object Retrieval and Its Parallel Implementation on GPU 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2011, 卷号: 13, 期号: 6, 页码: 1308-1318
作者:  Wang, Wenying;  Zhang, Dongming;  Zhang, Yongdong;  Li, Jintao;  Gu, Xiaoguang
收藏  |  浏览/下载:73/0  |  提交时间:2019/12/16
Affine transformations  GPU  object retrieval  parallel computing  
Restricted H.264/AVC video coding for privacy protected video scrambling 期刊论文
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2011, 卷号: 22, 期号: 6, 页码: 479-490
作者:  Dai, Feng;  Tong, Lingling;  Zhang, Yongdong;  Li, Jintao
收藏  |  浏览/下载:71/0  |  提交时间:2019/12/16
Coding efficiency  Drift error  H.264/AVC  Privacy protection  Restricted video coding  Security  Video surveillance  Video scrambling  
Graph-based multi-space semantic correlation propagation for video retrieval 期刊论文
VISUAL COMPUTER, 2011, 卷号: 27, 期号: 1, 页码: 21-34
作者:  Feng, Bailan;  Cao, Juan;  Bao, Xiuguo;  Bao, Lei;  Zhang, Yongdong;  Lin, Shouxun;  Yun, Xiaochun
收藏  |  浏览/下载:89/0  |  提交时间:2019/12/16
Concept-based video retrieval  Concept selection and fusion  Multi-space integration and propagation  Manifold ranking  
Multiview Spectral Embedding 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2010, 卷号: 40, 期号: 6, 页码: 1438-1446
作者:  Xia, Tian;  Tao, Dacheng;  Mei, Tao;  Zhang, Yongdong
收藏  |  浏览/下载:284/0  |  提交时间:2019/12/16
Dimensionality reduction  multiple views  spectral embedding  
On defining affinity graph for spectral clustering through ranking on manifolds 期刊论文
NEUROCOMPUTING, 2009, 卷号: 72, 期号: 13-15, 页码: 3203-3211
作者:  Xia, Tian;  Cao, Juan;  Zhang, Yong-dong;  Li, Jin-tao
收藏  |  浏览/下载:40/0  |  提交时间:2019/12/16
Affinity graph  Spectral clustering  Ranking on manifolds  
A density-based method for adaptive LDA model selection 期刊论文
NEUROCOMPUTING, 2009, 卷号: 72, 期号: 7-9, 页码: 1775-1781
作者:  Cao, Juan;  Xia, Tian;  Li, Jintao;  Zhang, Yongdong;  Tang, Sheng
收藏  |  浏览/下载:45/0  |  提交时间:2019/12/16
Latent Dirichlet allocation  Topic model  Topic