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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
西安光学精密机械研究... [5]
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OAI收割 [5]
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期刊论文 [5]
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2012 [3]
2011 [2]
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computer s... [5]
artificial... [3]
automation... [3]
cybernetic... [1]
electrical... [1]
engineerin... [1]
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学科主题:computer science
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Incremental threshold learning for classifier selection
期刊论文
OAI收割
neurocomputing, 2012, 卷号: 89, 页码: 89-95
作者:
Pang, Yanwei
;
Deng, Junping
;
Yuan, Yuan
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2012/09/03
Incremental learning
Threshold-based classifier
Classifier fusion
Object detection
Pattern recognition
Robust CoHOG Feature Extraction in Human-Centered Image/Video Management System
期刊论文
OAI收割
ieee transactions on systems man and cybernetics part b-cybernetics, 2012, 卷号: 42, 期号: 2, 页码: 458-468
作者:
Pang, Yanwei
;
Yan, He
;
Yuan, Yuan
;
Wang, Kongqiao
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2012/09/03
Co-occurrence histograms of oriented gradients (CoHOGs)
histograms of oriented gradients (HOGs)
human-centered image retrieval
human detection
Joint Learning for Single-Image Super-Resolution via a Coupled Constraint
期刊论文
OAI收割
ieee transactions on image processing, 2012, 卷号: 21, 期号: 2, 页码: 469-480
作者:
Gao, Xinbo
;
Zhang, Kaibing
;
Tao, Dacheng
;
Li, Xuelong
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  |  
浏览/下载:15/0
  |  
提交时间:2012/09/03
Grouping patch pairs (GPPs)
joint learning
neighbor embedding (NE)
super-resolution (SR)
Exploiting Local Coherent Patterns for Unsupervised Feature Ranking
期刊论文
OAI收割
ieee transactions on systems man and cybernetics part b-cybernetics, 2011, 卷号: 41, 期号: 6, 页码: 1471-1482
作者:
Huang, Qinghua
;
Tao, Dacheng
;
Li, Xuelong
;
Jin, Lianwen
;
Wei, Gang
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2012/06/29
Bicluster score
feature selection
unsupervised learning
Enhanced Biologically Inspired Model for Object Recognition
期刊论文
OAI收割
ieee transactions on systems man and cybernetics part b-cybernetics, 2011, 卷号: 41, 期号: 6, 页码: 1668-1680
作者:
Huang, Yongzhen
;
Huang, Kaiqi
;
Tao, Dacheng
;
Tan, Tieniu
;
Li, Xuelong
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  |  
浏览/下载:13/0
  |  
提交时间:2012/06/29
Biologically inspired model (BIM)
feedback
object recognition
sparseness