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» The Dark Side of Object Learning: Learning Objects
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156
Voted
ECCV
2008
Springer
15 years 5 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
128
Voted
CORR
1999
Springer
115views Education» more  CORR 1999»
15 years 3 months ago
The Symbol Grounding Problem
: There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This pa...
Stevan Harnad
199
Voted
CVPR
2009
IEEE
16 years 11 months ago
Recognition using Regions
This paper presents a unified framework for object detection, segmentation, and classification using regions. Region features are appealing in this context because: (1) they enco...
Chunhui Gu, Joseph J. Lim, Pablo Arbelaez, Jitendr...
151
Voted
CVPR
2005
IEEE
16 years 5 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
146
Voted
CVPR
2007
IEEE
16 years 5 months ago
Joint Optimization of Cascaded Classifiers for Computer Aided Detection
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
Murat Dundar, Jinbo Bi