Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is based on images taken in the field, 3D scanning,...

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Bibliographic Details
Main Authors:	B. Ambrus, G. Teschner, A.J. Kovács, M. Neményi, L. Helyes, Z. Pék, S. Takács, T. Alahmad, A. Nyéki
Format:	Article
Language:	English
Published:	Elsevier 2024-10-01
Series:	Heliyon
Subjects:	Tomato yield estimation Machine learning method Convolution neural network 3D point cloud shaping Approximation with sphere and 3D model Image segmentation and calibration
Online Access:	http://www.sciencedirect.com/science/article/pii/S2405844024140285

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http://www.sciencedirect.com/science/article/pii/S2405844024140285

Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

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