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» Discriminative Learning of Max-Sum Classifiers
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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
14 years 3 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
FLAIRS
2004
13 years 11 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
BMVC
2010
13 years 7 months ago
Insect Species Recognition using Sparse Representation
Insect species recognition is a typical application of image categorization and object recognition. Unlike generic image categorization datasets (such as the Caltech 101 dataset) ...
An Lu, Xin Hou, Chen Lin, Cheng-Lin Liu
ICIP
2010
IEEE
13 years 7 months ago
A dynamic threshold approach for skin segmentation in color images
: This paper presents a novel dynamic threshold approach to discriminate skin pixels and non-skin pixels in color images. Fixed decision boundaries (or fixed threshold) classificat...
Yogarajah Pratheepan, Joan Condell, Kevin Curran, ...
IJCV
2008
192views more  IJCV 2008»
13 years 9 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...