Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification-Reference-Cited by-同舟云学术

Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification

Published:2024-07-14 Issue: Volume:83 Page:1228-1236
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference
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Author:

Faria Fabio Augusto¹^ORCID,Buris Luiz Henrique¹^ORCID,Pereira Luis Augusto Martins¹^ORCID,Cappabianco Fabio Augusto Menocci¹^ORCID

Affiliation:

1. Institute of Science and Technology, Federal University of São Paulo, Sao Jose dos Campos, Sao Paulo, Brazil

Funder

the Sao Paulo Research Foundation (FAPESP)

the National Laboratory for Scientific Computing (LNCC/MCTI, Brazil) for providing HPC resources of the SDumont supercomputer

Publisher

ACM

Reference59 articles.

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2. Alexandre H. Aono, James S. Nagai, Gabriella da S. M. Dickel, Rafaela C. Marinho, Paulo E. A. M. de Oliveira, João P. Papa, and Fabio A. Faria. 2021. A stomata classification and detection system in microscope images of maize cultivars. PLOS ONE 16, 10 (10 2021), 1--17.

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4. B. E. Boser, I. M. Guyon, and V. N. Vapnik. 1992. A training algorithm for optimal margin classifiers. In Workshop on Computational Learning Theory (Pittsburgh, Pennsylvania, United States) (COLT '92). 144--152.

5. Luiz H. Buris, Daniel C. G. Pedronette, Joao P. Papa, Jurandy Almeida, Gustavo Carneiro, and Fabio A. Faria. 2022. Mixup-Based Deep Metric Learning Approaches for Incomplete Supervision. In 2022 IEEE International Conference on Image Processing (ICIP). 2581--2585.