Localización de hojas y frutos en plantas de jitomate mediante yolo8vn

José Luis Carranza Flores; Andrea Magadán Salazar; Jairo Cristóbal Alejo; Jorge Fuentes-Pacheco

doi:10.61117/ipsumtec.v8i3.383

Authors

José Luis Carranza Flores National Technological Institute of Mexico https://orcid.org/0000-0002-0235-8685
Andrea Magadán Salazar National Technological Institute of Mexico https://orcid.org/0000-0001-5474-4150
Jairo Cristóbal Alejo National Technological Institute of Mexico
Jorge Fuentes-Pacheco National Technological Institute of Mexico

DOI:

https://doi.org/10.61117/ipsumtec.v8i3.383

Keywords:

deep learning, CNN, YOLO8vn, tomato leaf, tomato fruit

Abstract

Locating objects of interest with deep learning is an area of computer vision that focuses on identifying and delineating the location of specific objects within an image. This article presents a proposal to locate the minimum rectangle of tomato leaves and fruits automatically, through image analysis with Yolo8vn. The results obtained show good performance even in the face of factors such as the presence of changes in perspective, scale, lighting, presence of dust, pathologies, etc.

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Author Biographies

José Luis Carranza Flores , National Technological Institute of Mexico

Jose Luis Carranza Flores holds a Master's degree in Computer Systems from the National Technological Institute of Mexico / Technological Institute of Acapulco. Areas of interest: machine learning, deep learning, precision agriculture.

Andrea Magadán Salazar , National Technological Institute of Mexico

Andrea Magadán Salazar holds a PhD in Information Technology and Computer Systems from Rey Juan Carlos University (Spain) and a Master of Science in Computer Science from TecNM/CENIDET. Her areas of interest in Artificial Intelligence are computer vision, machine learning, data science and deep learning in the fields of biometrics, video surveillance and precision agriculture for visual inspection of plants.

Jairo Cristóbal Alejo , National Technological Institute of Mexico

Jairo Cristóbal Alejo holds a PhD in Plant Pathology (Colegió de Postgraduados) and a Master's degree in Plant Pathology from the same institution, specialising in disease diagnosis and aetiology, epidemiology and disease control, and the use of beneficial microorganisms to improve plant health.

Jorge Fuentes-Pacheco , National Technological Institute of Mexico

Jorge Fuentes-Pacheco received his Master's and Doctorate degrees in Computer Science, specialising in Artificial Intelligence, from the National Centre for Research and Technological Development (CENIDET) in Mexico, in 2009 and 2014 respectively. During 2015 and 2016, he completed a postdoctoral fellowship at the Centre for Scientific Research (CInC) of the Autonomous University of the State of Morelos in Cuernavaca, Mexico. From September 2016 to September 2022, he served as a Professor-Researcher at CInC through the ‘CONACYT Chairs’ programme. He is currently a professor-researcher at the National Centre for Research and Technological Development (CENIDET). He has been recognised as a Level 1 National Researcher (January 2024-December 2028). His areas of interest are: Computer Vision, Precision Agriculture and Deep Learning.

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