Resumen

HERNANDEZ-CALVARIO, Omar; FLORIAN, Frida; SANCHEZ, María Guadalupe  y  AVILA-GEORGE, Himer. Counting of agave plants using convolutional neural networks with images acquired from an unmanned aerial vehicle. RISTI [online]. 2022, n.45, pp.64-76.  Epub 31-Mar-2022. ISSN 1646-9895.  https://doi.org/10.17013/risti.45.64-76.

This research provides new information by applying deep learning techniques in agave crops. The development of a deep learning algorithm based on convolutional neural networks that automates the count of agave plants in a crop from images taken from an unmanned aerial vehicle is intended, the count of agave plants will be obtained more efficient, economical and in a shorter period of time than the traditional way. The Project contributes to the solution of the preprocessing time of the images, improves the detection of agave plants with adversities, improves the training times of the algorithm, reduces computational costs.

Palabras clave : deep learning; convolutional neural networks (CNN); YOLOv5; precision agriculture; VANT.

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