Automatic Rice Plant Disease Evaluation Method Based on Anomaly Detection and Deep Learning-Reference-Cited by-同舟云学术

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Automatic Rice Plant Disease Evaluation Method Based on Anomaly Detection and Deep Learning

Published:2021-05-19 Issue: Volume: Page:
ISSN:
Container-title:2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)
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Author:

Tosawadi Teepakom,Kasetkasem Teerasit,Laungnarutai Wanlaya,Phatrapomnant Teera,Kumazawa Itsuo

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9454567/9454668/09454737.pdf?arnumber=9454737

Cited by 5 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. Using Deep Learning and Machine Learning: Real-Time Discernment and Diagnostics of Rice-Leaf Diseases in Bangladesh;EAI Endorsed Transactions on Internet of Things;2023-12-12

2. An efficient IoT based framework for detecting rice disease in smart farming system;Multimedia Tools and Applications;2023-04-28

3. Boundary-Based Rice-Leaf-Disease Classification and Severity Level Estimation for Automatic Insecticide Injection;Applied Engineering in Agriculture;2023

4. On the Use of Class Activation Map on Rice Blast Disease Identification and Localization;2022 19th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON);2022-05-24

5. Weather-based rice blast disease forecasting;Computers and Electronics in Agriculture;2022-02

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