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» Training of Classifiers Using Virtual Samples Only
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IJISTA
2007
124views more  IJISTA 2007»
13 years 9 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
ICRA
2008
IEEE
141views Robotics» more  ICRA 2008»
14 years 3 months ago
Tracking interacting targets with laser scanner via on-line supervised learning
— Successful multi-target tracking requires locating the targets and labeling their identities. For the laser based tracking system, the latter becomes significantly more challen...
Xuan Song, Jinshi Cui, Xulei Wang, Huijing Zhao, H...
TCSV
2008
313views more  TCSV 2008»
13 years 9 months ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
ICADL
2007
Springer
147views Education» more  ICADL 2007»
14 years 3 months ago
Feature Reinforcement Approach to Poly-lingual Text Categorization
With the rapid emergence and proliferation of Internet and the trend of globalization, a tremendous amount of textual documents written in different languages are electronically ac...
Chih-Ping Wei, Huihua Shi, Christopher C. Yang
PAMI
2006
206views more  PAMI 2006»
13 years 9 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang