| Full text | |
| Author(s): |
Afonso, Luis C. S.
;
Pedronette, Daniel C. G.
;
de Souza, Andre N.
;
Papa, Joao P.
;
IEEE
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR); v. N/A, p. 6-pg., 2018-01-01. |
| Abstract | |
Appropriate metrics are paramount for machine learning and pattern recognition. In Content-based Image Retrieval-oriented applications, low-level features and pairwise-distance metrics are usually not capable of representing similarity among the objects as observed by humans. Therefore, metric learning from available data has become crucial in such applications, but just a few related approaches take into account the contextual information inherent from the samples for a better accuracy performance. In this paper, we propose a novel approach which combines an unsupervised manifold learning algorithm with the Optimum-Path Forest (OPF) classifier to obtain more accurate recognition rates, as well as we show it can outperform standard OPF-based classifiers that are trained over the original manifold. Experiments conducted in some public datasets evidenced the validity of metric learning in the context of OPF classifiers. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 17/22905-6 - About image security using machine learning |
| Grantee: | Kelton Augusto Pontara da Costa |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 13/08645-0 - Re-Ranking and rank aggregation approaches for image retrieval tasks |
| Grantee: | Daniel Carlos Guimarães Pedronette |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 17/02286-0 - Probabilistic models for commercial losses detection |
| Grantee: | André Nunes de Souza |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 16/19403-6 - Energy-based learning models and their applications |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |