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Tomato Fruit Detection Using Modified Yolov5m Model with Convolutional Neural Networks

The farming industry is facing the major challenge of intensive and inefficient harvesting labors. Thus, an efficient and automated fruit harvesting system is required. In this study, three object classification models based on Yolov5m integrated with BoTNet, ShuffleNet, and GhostNet convolutional n...

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Detalles Bibliográficos
Autores principales: Tsai, Fa-Ta, Nguyen, Van-Tung, Duong, The-Phong, Phan, Quoc-Hung, Lien, Chi-Hsiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10489844/
https://www.ncbi.nlm.nih.gov/pubmed/37687314
http://dx.doi.org/10.3390/plants12173067