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IJISTA
2007
124views more  IJISTA 2007»
15 years 6 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...
TITS
2008
250views more  TITS 2008»
15 years 6 months ago
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
This paper presents two different types of visual activity analysis modules based on vehicle tracking. The highway monitoring module accurately classifies vehicles into eight diffe...
Brendan Tran Morris, Mohan M. Trivedi
ESANN
2006
15 years 8 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
CVPR
2008
IEEE
16 years 8 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona
ICCV
2003
IEEE
16 years 8 months ago
Learning a Classification Model for Segmentation
We propose a two-class classification model for grouping. Human segmented natural images are used as positive examples. Negative examples of grouping are constructed by randomly m...
Xiaofeng Ren, Jitendra Malik