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Large Scale Support Vector Machines Algorithms for Visual Recognition

 

Marketed By :  Scholars' Press   Sold By :  Kamal Books International  
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  • Product Description
 

Visual recognition remains an extremely challenging problem in computer vision. Most previous approaches have been evaluated on small datasets. However, ImageNet dataset with millions images for thousands classes poses more challenges for the next generation of vision mechanisms. Learning an efficient visual classifier and constructing a robust visual representation in a large scale scenario are two main research issues. In this book, we present how to tackle these issues. Firstly, a novel approach is presented by using several local descriptors to improve the discriminative power of image representation. Secondly, the state-of-the-art SVMs are extended by building the balanced bagging classifiers with sampling strategy and parallelizing the training process with several multi-core computers. Thirdly, the binary stochastic gradient descent SVM is developed to the new multiclass SVM for efficiently classifying large image datasets into many classes. Finally, when the training data cannot fit into computer memory, the training task of SVM becomes more complicated to deal with. This challenge is addressed by an incremental learning method for both large scale linear and nonlinear SVMs

Product Specifications
SKU :COC54907
AuthorThanh-Nghi Doan and Francois Poulet
LanguageEnglish
BindingPaperback
Number of Pages164
Publishing Year2014-05-06T00:00:00.000
ISBN9783639715750
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandScholars' Press
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-06-08 00:00:00