Publications

@article{sanchez-gonzalez_use_2018,

title = {Use of classifiers and recursive feature elimination to assess boar sperm viability},

author = {Lidia Sánchez-González and Laura Fernández-Robles and Manuel Castejón-Limas and Javier Alfonso-Cendón and Hilde Pérez and Hector Quintián-Pardo and Emilio Corchado-Rodríguez},

url = {https://academic.oup.com/jigpal/article-abstract/26/6/629/5092723?login=true},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Logic Journal of the IGPL},

volume = {26},

number = {6},

pages = {629–637},

abstract = {This paper evaluates the use of various classifiers to assess boar sperm cells and discriminate between intact or reacted acrosomes for fertility purposes. It also investigates the feasibility of applying dimension-reduction techniques to simplify the classification process. Four supervised classifiers were used: Extremely Randomized Trees, Random Forest, Support Vector Machines, and Gaussian Naive Bayes. The datasets contain features related to local gradients, gray levels, and standard deviations along sperm cell contours. The experiments showed that only 5 features out of 840 were needed for satisfactory results, as determined by veterinary experts.},

note = {Publisher: Oxford University Press},

keywords = {Acrosome Reaction, Boar Sperm Cells, Classifiers, Dimension Reduction},

pubstate = {published},

tppubtype = {article}

}