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Cattle breed identification and live weight evaluation the basis of machine learning and computer vision

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dc.contributor.authorMegel, Y. E.
dc.contributor.authorRudenko, O. G.
dc.contributor.authorBezsonov, O. O.
dc.contributor.authorRybalka, A. I.
dc.date.accessioned2021-12-28T15:14:13Z
dc.date.available2021-12-28T15:14:13Z
dc.date.issued2020
dc.description.abstractThe problem of the cow’s live weight estimation is considered. A convolutional neural network based method for animal recognition and its breed identification in combination with epipolar geometry approach for object’s size measurement is proposed. Information regarding animal’s size and its breed is further used for LW estimation by multilayer perceptron based predictive model. This approach can be used to replace traditional methods of direct observation and measurement. The proposed system can be widely used in the management of a modern farm. Accuracy and performance of the proposed method has been tested with the participation of the experts.uk_UA
dc.identifier.citationCattle breed identification and live weight evaluation the basis of machine learning and computer vision / Y. E. Megel, O. G. Rudenko, O. O. Bezsonov, A. I. Rybalka // Third International Workshop on Computer Modeling and Intelligent Systems (CMIS-2020), held in Zaporizhzhia, Ukraine, April-May, 2020. – P. 46–61.uk_UA
dc.identifier.issn1613-0073
dc.identifier.urihttps://openarchive.nure.ua/handle/document/18827
dc.language.isoenuk_UA
dc.publisherНаціональний університет "Запорізька політехніка"uk_UA
dc.subjectconvolutional neural networks (CNN)uk_UA
dc.subjectepipolar geometryuk_UA
dc.subjectimage processinguk_UA
dc.subjectcomputer visionuk_UA
dc.subjectcowuk_UA
dc.subjectmask-rcnnuk_UA
dc.titleCattle breed identification and live weight evaluation the basis of machine learning and computer visionuk_UA
dc.typeArticleuk_UA
dspace.entity.typePublication

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