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» Learning and using taxonomies for fast visual categorization
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WWW
2008
ACM
15 years 10 months ago
Floatcascade learning for fast imbalanced web mining
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Xiaoxun Zhang, Xueying Wang, Honglei Guo, Zhili Gu...
ICPR
2008
IEEE
15 years 11 months ago
Joint visual vocabulary for animal classification
This paper presents a method for visual object categorization based on encoding the joint textural information in objects and the surrounding background, and requiring no segmenta...
Alireza Tavakoli Targhi, Andrzej Pronobis, Heydar ...
ICCV
2011
IEEE
13 years 9 months ago
Annotator Rationales for Visual Recognition
Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
Jeff Donahue, Kristen Grauman
CORR
2008
Springer
170views Education» more  CORR 2008»
14 years 9 months ago
Fast Wavelet-Based Visual Classification
We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work [13]. Specifically, trading-off biological accuracy for comput...
Guoshen Yu, Jean-Jacques E. Slotine
ICCV
2009
IEEE
14 years 7 months ago
Learning image similarity from Flickr groups using Stochastic Intersection Kernel MAchines
Measuring image similarity is a central topic in computer vision. In this paper, we learn similarity from Flickr groups and use it to organize photos. Two images are similar if th...
Gang Wang, Derek Hoiem, David A. Forsyth