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ESANN
2006

Classification of Boar Sperm Head Images using Learning Vector Quantization

14 years 1 months ago
Classification of Boar Sperm Head Images using Learning Vector Quantization
We apply Learning Vector Quantization (LVQ) in automated boar semen quality assessment. The classification of single boar sperm heads into healthy (normal) and non-normal ones is based on grey-scale microscopic images only. Sample data was classified by veterinary experts and is used for training a system with a number of prototypes for each class. We apply as training schemes Kohonen's LVQ1 and the variants Generalized LVQ (GLVQ) and Generalized Relevance LVQ (GRLVQ). We compare their performance and study the influence of the employed metric.
Michael Biehl, Piter Pasma, Marten Pijl, Lidia S&a
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2006
Where ESANN
Authors Michael Biehl, Piter Pasma, Marten Pijl, Lidia Sánchez, Nicolai Petkov
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