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TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
CVPR
2010
IEEE
14 years 3 months ago
Grouplet: a Structured Image Representation for Recognizing Human and Object Interactions
Psychologists have proposed that many human-object interaction activities form unique classes of scenes. Recognizing these scenes is important for many social functions. To enable...
Bangpeng Yao, Li Fei-Fei
GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
13 years 11 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
ISCIS
2005
Springer
14 years 28 days ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
ICCV
2011
IEEE
12 years 9 months ago
Segmentation as Selective Search for Object Recognition
Software available at http://disi.unitn.it/~uijlings or http://koen.me/research/ For object recognition, the current state-of-the-art is based on exhaustive search. However, to ...
K van de Sande, J Uijlings, T Gevers, A Smeulders