Review of deep learning-based methods for non-destructive evaluation of agricultural products-Reference-Cited by-同舟云学术

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Review of deep learning-based methods for non-destructive evaluation of agricultural products

Published:2024-09 Issue: Volume:245 Page:56-83
ISSN:1537-5110
Container-title:Biosystems Engineering
language:en
Short-container-title:Biosystems Engineering

Author:

Li Zhenye^ORCID,Wang Dongyi^ORCID,Zhu Tingting,Tao Yang,Ni Chao

Publisher

Elsevier BV

Reference223 articles.

1. Tomato plant disease detection using transfer learning with C-GAN synthetic images;Abbas;Computers and Electronics in Agriculture,2021

2. Nutrient status diagnosis of infield oilseed rape via deep learning-enabled dynamic model;Abdalla;IEEE Transactions on Industrial Informatics,2021

3. An optimized capsule neural networks for tomato leaf disease classification: EURASIP journal on image & video processing;Abouelmagd;EURASIP Journal on Image & Video Processing,2024

4. Interactive deep learning for shelf life prediction of muskmelons based on an active Learning approach;Albert-Weiss;Sensors,2022

5. An improved pear disease classification approach using cycle generative adversarial network: Scientific Reports;Alshammari;Scientific Reports,2024

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. PlanteSaine: An Artificial Intelligent Empowered Mobile Application for Pests and Disease Management for Maize, Tomato, and Onion Farmers in Burkina Faso;Agriculture;2024-07-30

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