Actas de congresos
Automatic classification of fish germ cells through optimum-path forest
Fecha
2011-12-26Registro en:
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, p. 5084-5087.
1557-170X
10.1109/IEMBS.2011.6091259
WOS:000298810004007
2-s2.0-84055193445
9039182932747194
9581468058921952
3150094336796923
Autor
Universidade Estadual Paulista (Unesp)
Southwest Paulista College
Institución
Resumen
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.