| Title: | OS20-4 General Image Categorization Using Collaborative Mean Attraction |
|---|---|
| Publication: | ICAROB2017 |
| Volume: | 22 |
| Pages: | 315-318 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2017.OS20-4 |
| Author(s): | Hiroki Ogihara, Masayuki Mukunoki |
| Publication Date: | January 19, 2017 |
| Keywords: | Generic Object Recognition, CMA method, ImageNet, Caltech dataset |
| Abstract: | In this paper, we apply Collaborative Mean Attraction (CMA) method, which has been developed for person reidentification problem, to general image categorization problem. Experimental results using Caltech101 and Caltech256 dataset reveal that CMA shows better categorization accuracy than traditional methods, particularly in the case when the size of training data is small. Furthermore, we discuss the parameter settings for CMA through several experiments. |
| PDF File: | https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS20/OS20-4.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
(c)2008 Copyright The Regents of ALife Robotics Corporation Ltd. All Rights Reserved.