Skip navigation
Skip navigation

Classification and Boosting with Multiple Collaborative Representations

Chi, Yuejie; Porikli, Fatih

Description

Recent advances have shown a great potential to explore collaborative representations of test samples in a dictionary composed of training samples from all classes in multi-class recognition including sparse representations. In this paper, we present two

CollectionsANU Research Publications
Date published: 2014
Type: Journal article
URI: http://hdl.handle.net/1885/36124
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2013.236

Download

File Description SizeFormat Image
01_Chi_Classification_and_Boosting_2014.pdf1.88 MBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  23 August 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator