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» Feature selection based on the training set manipulation
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ICCV
2005
IEEE
14 years 1 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla
SAMT
2009
Springer
176views Multimedia» more  SAMT 2009»
14 years 2 months ago
Shape-Based Autotagging of 3D Models for Retrieval
This paper describes an automatic annotation, or autotagging, algorithm that attaches textual tags to 3D models based on their shape and semantic classes. The proposed method emplo...
Ryutarou Ohbuchi, Shun Kawamura
KBS
2008
98views more  KBS 2008»
13 years 6 months ago
Mixed feature selection based on granulation and approximation
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Qinghua Hu, Jinfu Liu, Daren Yu
FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
14 years 2 months ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
ICPR
2004
IEEE
14 years 8 months ago
Training of Classifiers Using Virtual Samples Only
This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifiers, a support vector machine and a polynomial c...
Annika Kuhl, Lars Krüger, Christian Wöhl...