YOLO-FLBM: a lightweight and high-performance model for tomato ripeness detection in complex greenhouse environments

Real-time detection of tomato ripeness in complex greenhouse environments presents a significant dual challenge: the interference caused by foliage occlusion and fruit overlapping demands high detection accuracy, while the limited computational resources of harvesting robots necessitate model lightw...

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Detalles Bibliográficos

Autores principales:	Yuting Su, Peijun Zhang, Huicheng Li, Feng Kang, Pushi Zhao, Lijin Wang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Frontiers Media S.A. 2026-06-01
Colección:	Frontiers in Plant Science
Materias:	complex field environment lightweight model ripeness detection tomato object detection YOLOv8s
Acceso en línea:	https://www.frontiersin.org/articles/10.3389/fpls.2026.1824558/full
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