Abstract

Phenotypic evaluation of Brown Swiss cows is a method used in the Peruvian Andean Region to identify and select breeding females. Selection is based on their closeness to ideal dairy conformation. This task is perform by a specialists in stock judging. Under this context, the aim of the present study was to demonstrate the feasibility to perform a partial phenotypic evaluation of Brown Swiss cows by overlapping templates through development of a cow detection model and a decision making support system for identification and automatic classification of Brown Swiss cattle. TensorFlow Object Detection API was used to detect the cow in real time. The learning transfer approach was used for training, and MobilNet was selected as a pre-trained architecture. As result a mobile app was developed to determine whether an animal has Brown Swiss breed phenotypic characteristics through an automatic adjustment and calibration of a cow's template.

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