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» Learning Color Names from Real-World Images
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ISBI
2011
IEEE
12 years 11 months ago
Group sparsity based classification for cervigram segmentation
This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, usi...
Yang Yu, Junzhou Huang, Shaoting Zhang, Christophe...
CVPR
2003
IEEE
14 years 9 months ago
Video-Based Face Recognition Using Probabilistic Appearance Manifolds
This paper presents a novel method to model and recognize human faces in video sequences. Each registered person is represented by a low-dimensional appearance manifold in the amb...
Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David...
CORR
2004
Springer
144views Education» more  CORR 2004»
13 years 7 months ago
The Google Similarity Distance
Words and phrases acquire meaning from the way they are used in society, from their relative semantics to other words and phrases. For computers the equivalent of `society' is...
Rudi Cilibrasi, Paul M. B. Vitányi
FGR
2000
IEEE
159views Biometrics» more  FGR 2000»
14 years 2 days ago
Gesture Modeling and Recognition Using Finite State Machines
This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
Pengyu Hong, Thomas S. Huang, Matthew Turk
CIKM
2008
Springer
13 years 9 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan