Automatic classification of fish germ cells through optimum-path forest
Author
Date
2011-12-26Type
Conference paper
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Open access 

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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.
How to cite this document
Papa, João Paulo et al. Automatic classification of fish germ cells through optimum-path forest. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, p. 5084-5087. Available at: <http://hdl.handle.net/11449/73085>.
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English

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