Deep Learning-Based Multistage Peach Ripeness Detection with Data Leakage Mitigation and Real-World Validation

Accurate fruit ripeness assessment is essential for optimizing harvest timing and ensuring postharvest quality, particularly in climacteric fruits such as peaches, which exhibit rapid and heterogeneous ripening. This study proposes a deep learning-based approach for multistage peach ripeness classif...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Salvador Castro-Tapia, Germán Díaz-Florez, Rafael Reveles-Martínez, Héctor A. Guerrero-Osuna, Luis F. Luque-Vega, Humberto Morales-Magallanes, Jorge Pablo Vega-Borrego, Gilberto Vázquez-García, Carlos A. Olvera-Olvera
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	MDPI AG 2026-05-01
Σειρά:	Applied Sciences
Θέματα:	peach ripeness detection AlexNet EfficientNet YOLOv8 YOLOv11 YOLOv12
Διαθέσιμο Online:	https://www.mdpi.com/2076-3417/16/9/4484
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