Tomato seedling stem and leaf segmentation method based on an improved ResNet architecture

IntroductionThe phenotypic traits of tomato plants reflect their growth status, and investigating these characteristics can improve tomato production. Traditional deep learning models face challenges such as excessive parameters, high complexity, and susceptibility to overfitting in point cloud segm...

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Bibliografische Detailangaben

Hauptverfasser:	Lina Zhang, Xinying Li, Zhiyin Yang, Bo Yang, Shengpeng Yu, Shuai Zhao, Ziyi Huang, Xingrui Zhang, Han Yang, Yixing Lin, Helong Yu, Minglai Yang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Frontiers Media S.A. 2025-08-01
Schriftenreihe:	Frontiers in Plant Science
Schlagworte:	plant phenotype stem and leaf segmentation in point cloud lightweight network bottleneck block downsampling
Online-Zugang:	https://www.frontiersin.org/articles/10.3389/fpls.2025.1571445/full
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