Application of X-Ray Imaging and Convolutional Neural Networks in the Prediction of Tomato Seed Viability

Application of X-Ray Imaging and Convolutional Neural Networks in the Prediction of Tomato Seed Viability

Tomato fruits are consumed worldwide owing to their health benefits, taste, and flavor. In tomato cultivation, seed viability is directly related to crop productivity. Currently, the methods used to evaluate seed viability involve destructive sampling tests; accordingly, nondestructive methods for p...

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Bibliographic Details
Main Authors: Suk-Ju Hong, Seongmin Park, Chang-Hyup Lee, Sungjay Kim, Seung-Woo Roh, Nandita Irsaulul Nurhisna, Ghiseok Kim
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
X-ray image
tomato
seed viability
deep learning
convolutional neural networks
Online Access:https://ieeexplore.ieee.org/document/10098590/

Internet

https://ieeexplore.ieee.org/document/10098590/

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