DPDB-YOLO: A lightweight YOLOv13 cherry tomato ripeness detection method with adaptive extraction module and multi-scale feature fusion architecture

In this paper, we propose a lightweight and efficient cherry tomato ripeness detection model, named DPDB-YOLO, based on YOLOv13n, for fast and accurate detection in natural environments. The improvements are as follows: first, the DPC3k2 (DWConv+PConv+C3k2) module replaces the DSC3k2 module in the b...

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Detalhes bibliográficos

Principais autores:	Haojie Jia, Lijuan Zhang, Xuemei Liang, Pengwei Yin, Haohai You, Dongming Li
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2025-12-01
coleção:	Industrial Crops and Products
Assuntos:	DPDB-YOLO Lightweight Cherry tomato Ripeness detection Deep learning
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S0926669025019661
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