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Type: | Artigo |
Title: | Optimum-path Forest Based On K-connectivity: Theory And Applications Optimum-path forest based on k-connectivity : theory and applications |
Author: | Papa, João Paulo Nachif Fernandes, Silas Evandro Falcao, Alexandre Xavier |
Abstract: | Graph-based pattern recognition techniques have been in the spotlight for many years, since there is a constant need for faster and more effective approaches. Among them, the Optimum-Path Forest (OPF) framework has gained considerable attention in the last years, mainly due to the promising results obtained by OPF-based classifiers, which range from unsupervised, semi-supervised and supervised learning. In this paper, we consider a deeper theoretical explanation concerning the supervised OPF classifier with k-neighborhood (OPFk), as well as we proposed two different training and classification algorithms that allow OPFk to work faster. The experimental validation against standard OPF and Support Vector Machines also validates the robustness of OPFk in real and synthetic datasets. (C) 2016 Elsevier B.V. All rights reserved. Graph-based pattern recognition techniques have been in the spotlight for many years, since there is a constant need for faster and more effective approaches. Among them, the Optimum-Path Forest (OPF) framework has gained considerable attention in the las |
Subject: | Pattern Classification Optimum-path Forest Supervised Learning Reconhecimento de padrões Floresta de caminhos ótimos Aprendizado de máquina Inteligência artificial |
Country: | Países Baixos |
Editor: | Elsevier |
Citation: | Pattern Recognition Letters. Elsevier Science Bv, v. 87, p. 117 - 126, 2017. |
Rights: | fechado Fechado |
Identifier DOI: | 10.1016/j.patrec.2016.07.026 |
Address: | https://www.sciencedirect.com/science/article/pii/S0167865516302057 |
Date Issue: | 2017 |
Appears in Collections: | IC - Artigos e Outros Documentos |
Files in This Item:
File | Size | Format | |
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000395616700015.pdf | 1.66 MB | Adobe PDF | View/Open |
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