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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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 |