Publicação: Automatic classification of fish germ cells through optimum-path forest
Nenhuma Miniatura disponível
Data
2011-12-26
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Tipo
Trabalho apresentado em evento
Direito de acesso
Acesso aberto
Resumo
The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.
Descrição
Idioma
Inglês
Como citar
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, p. 5084-5087.
