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CVPR
2009
IEEE
15 years 5 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
CVPR
2009
IEEE
1976views Computer Vision» more  CVPR 2009»
15 years 5 months ago
Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification
Recently SVMs using spatial pyramid matching (SPM) kernel have been highly successful in image classification. Despite its popularity, these nonlinear SVMs have a complexity O(n...
Jianchao Yang, Kai Yu, Yihong Gong, Thomas S. Huan...
CVPR
2009
IEEE
15 years 5 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
ICCV
2009
IEEE
1188views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Actionable Information in Vision
I propose a notion of visual information as the complexity not of the raw images, but of the images after the effects of nuisance factors such as viewpoint and illumination are dis...
Stefano Soatto
CVPR
2004
IEEE
15 years 8 hour ago
Hidden Semantic Concept Discovery in Region Based Image Retrieval
This paper addresses Content Based Image Retrieval (CBIR), focusing on developing a hidden semantic concept discovery methodology to address effective semanticsintensive image ret...
Ruofei Zhang, Zhongfei (Mark) Zhang