Application Development for a Project using Flutter

Plant disease detection consumes more time and money for farmers and also manual detection errors may also lead to low crop cultivation rate. The proposed study has used the YOLO V3 demonstration with a transfer learning approach to identify the infections in photos of betel leaves. To significantly...

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Bibliographic Details
Published in:2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) pp. 947 - 951
Main Authors: Nagaraj, K, Prabakaran, B, Ramkumar, M.O
Format: Conference Proceeding
Language:English
Published: IEEE 20.10.2022
Subjects:
Crops
Cross-platform apps
Dart
Diseases
Flutter
Manuals
Object oriented programming
Object-oriented programming language
Postal services
Task analysis
Transfer learning
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Summary:Plant disease detection consumes more time and money for farmers and also manual detection errors may also lead to low crop cultivation rate. The proposed study has used the YOLO V3 demonstration with a transfer learning approach to identify the infections in photos of betel leaves. To significantly increase betel leaf cultivation, the diseases should be identified at an early stage before it spreads to the entire field. The proposed betel leaf disease detection strategy accomplishes a proper balance of exactness and recognition speed. The parameters of the suggested demonstration were adjusted for the classification task, and a high level of precision of around 95.6% was attained.
DOI:10.1109/ICOSEC54921.2022.9951938