Clasificación Morfológica del Caballo Peruano de Paso mediante Modelos Pre-Entrenados de Inteligencia Artificial

Luis José A. Sáenz Ráez · Zenodo (CERN European Organization for Nuclear Research) (2026) · DOI: 10.5281/zenodo.19600220

Resumen

This manuscript, in spanish, presents a didactic and technical approach to the morphological classification of Peruvian Paso Horses using pre-trained Artificial Intelligence algorithms. It emphasizes methodological foundations and practical applications in agroindustry and animal science, serving as a concise reference for researchers and professionals. The approach can be extended to other horse breeds and animal species, broadening its relevance in livestock evaluation. The study employs supervised learning techniques and transfer learning with pre-trained convolutional neural networks, combined with image processing and statistical validation tools. These methods ensure reliable morphological classification and demonstrate the potential of AI-based frameworks for broader applications in animal science and agroindustry.

Instituciones: Universidad Científica del Perú