Future trends in optimum-path forest classification

• Autor(a) principal: Papa, João Paulo [UNESP]
• Data de Publicação: 2022
• Outros Autores: Falcão, Alexandre Xavier
• Tipo de documento: Capítulo de livro
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/B978-0-12-822688-9.00017-7; http://hdl.handle.net/11449/242086
• topic: Clustering; Deep learning; Machine learning; Optimum-path forest; Supervised learning

In the past years, we have observed an increasing number of applications that require machine learning techniques to sort out problems that are not straightforward to humans. The reasons vary from information that is not clearly visible to the human eye (e.g., microscopic patterns in medical images) or the massive amount of data to analyze. This book aimed to shed light on the Optimum-Path Forest framework, which comprises approaches to dealing with supervised, semi-supervised, and unsupervised learning. Different applications have been presented together with a theoretical background concerning the techniques presented here. We expect to call the attention and curiosity of the readers towards OPF-based techniques and their strengths. © 2022 Copyright