Application of the convolutional network Mask R-CNN for the estimation of the body weight of the guinea pig

Ormeño-Ayala Y.I.; Zapata-Ttito A.G. · Revista Cientifica de Sistemas e Informatica (2024) · DOI: 10.51252/rcsi.v4i1.614

Resumen

Artificial intelligence can contribute in tracking the productive cycle of the cuy through the application of convolutional networks, being a necessity the estimation of its weight. This study focused on the application of the Mask R-CNN convolutional network, using a mobile application as a tool for image capture. The methodology covered the following stages: i) bibliographic review, ii) data collection (images and pig weights), iii) image processing through data augmentation, iv) construction of a dataset (image selection and data transformation);, v) adaptation and training of the convolutional network, vi) analysis of the results to validate its performance, and finally, vii) implementation of a mobile application as a weight estimation tool. A set of 6244 pig images with their respective weights and masks was managed to be collected, together with the Mask R-CNN network adaptation. These tasks led to a correlation of R2 = 80.2% with the validation set, as well as to the development of a functional prototype capable of estimating the weight of pigs using the camera of a cell phone.

Instituciones: Universidad Nacional de San Antonio Abad del Cusco