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- W2527598789 abstract "This paper employs well-known techniques as Support Vector Machines and Neural Networks in order to classify images of boar sperm cells. Acrosome integrity gives information about if a sperm cell is able to fertilize an oocyte. If the acrosome is intact, the fertilization is possible. Otherwise, if a sperm cell has already reacted and has lost its acrosome or even if it is going through the capacitation process, such sperm cell has lost its capability to fertilize. Using a set of descriptors already proposed to describe the acrosome state of a boar sperm cell image, two different classifiers are considered. Results show the classification accuracy improves previous results." @default.
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- W2527598789 date "2016-10-01" @default.
- W2527598789 modified "2023-10-02" @default.
- W2527598789 title "Use of Support Vector Machines and Neural Networks to Assess Boar Sperm Viability" @default.
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- W2527598789 doi "https://doi.org/10.1007/978-3-319-47364-2_2" @default.
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