An improved YOLOv7 model based on Swin Transformer and Trident Pyramid Networks for accurate tomato detection

Accurate fruit detection is crucial for automated fruit picking. However, real-world scenarios, influenced by complex environmental factors such as illumination variations, occlusion, and overlap, pose significant challenges to accurate fruit detection. These challenges subsequently impact the comme...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Guoxu Liu, Yonghui Zhang, Jun Liu, Deyong Liu, Chunlei Chen, Yujie Li, Xiujie Zhang, Philippe Lyonel Touko Mbouembe
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Frontiers Media S.A. 2024-09-01
Schriftenreihe:	Frontiers in Plant Science
Schlagworte:	tomato detection YOLOv7 Swin Transformer Trident Pyramid Network Focaler-IoU
Online-Zugang:	https://www.frontiersin.org/articles/10.3389/fpls.2024.1452821/full
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