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» Combinations of Weak Classifiers
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CLOR
2006
14 years 1 months ago
Comparison of Generative and Discriminative Techniques for Object Detection and Classification
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
Ilkay Ulusoy, Christopher M. Bishop
ICPR
2010
IEEE
13 years 8 months ago
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations
Classifying images using features extracted from densely sampled local patches has enjoyed significant success in many detection and recognition tasks. It is also well known that ...
Mert Dikmen, Thomas S. Huang
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 11 months ago
Class-Specific Ensembles for Active Learning
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Amit Mandvikar, Huan Liu
CVPR
2005
IEEE
14 years 3 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
SIGSOFT
2004
ACM
14 years 3 months ago
Variability management with feature-oriented programming and aspects
This paper presents an analysis of feature-oriented and aspectoriented modularization approaches with respect to variability management as needed in the context of system families...
Mira Mezini, Klaus Ostermann