Semantic Segmentation Method for High-Resolution Tomato Seedling Point Clouds Based on Sparse Convolution

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Detalles Bibliográficos
Publicado en:	Agriculture vol. 15, no. 1 (2025), p. 74
Autor Principal:	Li, Shizhao
Outros autores:	Yan, Zhichao, Ma, Boxiang, Guo, Shaoru, Song, Hongxia
Publicado:	MDPI AG
Materias:	Hexagon Metrology Datasets Deep learning Agricultural production Image resolution Noise reduction Scanners Tomatoes Convolution Leaves Image processing Semantic segmentation Modules Training Soil improvement Semantics Seedlings Image segmentation Phenotyping Lasers Neural networks Stems High resolution Three dimensional models Inference Diffusion rate Encoding-Decoding Environmental
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