Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{daSilva2012510,

• author = "Andre Tavares {da Silva} and Jefersson Alex {dos Santos} and Alexandre Xavier Falcao and Ricardo {da S. Torres} and Leo Pini Magalhaes",
• title = "Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning",
• journal = "Computer Vision and Image Understanding",
• volume = "116",
• number = "4",
• pages = "510--523",
• year = "2012",
• ISSN = "1077-3142",
• DOI = "doi:10.1016/j.cviu.2011.12.001",
• URL = "http://www.sciencedirect.com/science/article/pii/S107731421100261X",
• keywords = "genetic algorithms, genetic programming, Content-based image retrieval, Optimum-path forest classifiers, Composite descriptor, Multi-scale parameter search, Image pattern analysis",
• abstract = "In content-based image retrieval (CBIR) using feedback-based learning, the user marks the relevance of returned images and the system learns how to return more relevant images in a next iteration. In this learning process, image comparison may be based on distinct distance spaces due to multiple visual content representations. This work improves the retrieval process by incorporating multiple distance spaces in a recent method based on optimum-path forest (OPF) classification. For a given training set with relevant and irrelevant images, an optimisation algorithm finds the best distance function to compare images as a combination of their distances according to different representations. Two optimisation techniques are evaluated: a multi-scale parameter search (MSPS), never used before for CBIR, and a genetic programming (GP) algorithm. The combined distance function is used to project an OPF classifier and to rank images classified as relevant for the next iteration. The ranking process takes into account relevant and irrelevant representatives, previously found by the OPF classifier. Experiments show the advantages in effectiveness of the proposed approach with both optimisation techniques over the same approach with single distance space and over another state-of-the-art method based on multiple distance spaces.",

}

Genetic Programming entries for Andre Tavares da Silva Jefersson Alex dos Santos Alexandre X Falcao Ricardo da Silva Torres Leo Pini Magalhaes

Citations