| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Estado Rio de Janeiro, Inst Politecn Rio de Janeiro, BR-28601970 Nova Friburgo, RJ - Brazil
[2] Univ Sao Paulo, IFSC, BR-13560970 Sao Carlos, SP - Brazil
[3] Univ Fed Rio de Janeiro, Inst Biofis Carlos Chagas Filho, BR-21941902 Rio De Janeiro, RJ - Brazil
Total Affiliations: 3
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| Document type: | Journal article |
| Source: | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 391, n. 19, p. 4487-4496, OCT 1 2012. |
| Web of Science Citations: | 7 |
| Abstract | |
This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shannon entropy for general pattern recognition, and proposes a multi-q approach to improve pattern analysis using entropy. A series of experiments were carried out for the problem of classifying image patterns. Given a dataset of 40 pattern classes, the goal of our image case study is to assess how well the different entropies can be used to determine the class of a newly given image sample. Our experiments show that the Tsallis entropy using the proposed multi-q approach has great advantages over the Boltzmann-Gibbs-Shannon entropy for pattern classification, boosting image recognition rates by a factor of 3. We discuss the reasons behind this success, shedding light on the usefulness of the Tsallis entropy and the multi-q approach. (C) 2012 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 11/01523-1 - Computer vision methods applied to the identification and analysis of plants |
| Grantee: | Odemir Martinez Bruno |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 10/08614-0 - Static and Dynamic Texture Analysis and their Applications in Biology and Nanotechnology |
| Grantee: | Wesley Nunes Gonçalves |
| Support Opportunities: | Scholarships in Brazil - Doctorate |