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https://hdl.handle.net/10216/81654Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | João Paulo Papa | |
| dc.creator | Willian Paraguassu Amorim | |
| dc.creator | Alexandre Xavier Falcão | |
| dc.creator | João Manuel R. S. Tavares | |
| dc.date.accessioned | 2025-09-30T23:33:09Z | - |
| dc.date.available | 2025-09-30T23:33:09Z | - |
| dc.date.issued | 2015 | |
| dc.identifier.other | sigarra:107756 | |
| dc.identifier.uri | https://hdl.handle.net/10216/81654 | - |
| dc.description.abstract | Although one can find several pattern recognition techniques out there, there is still room for improvements and new approaches. In this book chapter, we revisited the Optimum-Path Forest (OPF) classifier, which has been evaluated over the last years in a number of applications that consider supervised, semi-supervised and unsupervised learning problems. We also presented a brief compilation of a number of previous works that employed OPF in different research fields, that range from remote sensing image classification to medical data analysis. (c) 2016 by World Scientific Publishing Co. Pte. Ltd. | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Handbook Of Pattern Recognition And Computer Vision (5th Edition) | |
| dc.rights | openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Ciências Tecnológicas, Ciências da engenharia e tecnologias | |
| dc.subject | Technological sciences, Engineering and technology | |
| dc.title | Recent advances on optimum-path forest for data classification: Supervised, semi-supervised, and unsupervised learning | |
| dc.type | Capítulo ou Parte de Livro | |
| dc.contributor.uporto | Faculdade de Engenharia | |
| dc.identifier.doi | 10.1142/9789814656535_0006 | |
| dc.identifier.authenticus | P-00V-MVV | |
| dc.subject.fos | Ciências da engenharia e tecnologias | |
| dc.subject.fos | Engineering and technology | |
| Appears in Collections: | FEUP - Capítulo ou Parte de Livro | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 107756.pdf | Chapter | 727.56 kB | Adobe PDF | ![]() View/Open |
This item is licensed under a Creative Commons License
