Improving wheat leaf disease classification : Evaluating augmentation strategies and CNN-Based models with limited dataset

Improving wheat leaf disease classification : Evaluating augmentation strategies and CNN-Based models with limited dataset

Global food security is seriously threatened by wheat leaf disease, which makes effective and precise disease detection and classification techniques necessary. For efficient disease control and the best possible crop health, timely identification and precise classification are essential. However, t...

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Bibliographic Details
Main Authors: Ramadan, Syed Taha Yeasin, Sakib, Tanjim, Farid, Fahmid Al, Islam, Md Shofiqul, Junaidi, Abdullah, Bhuiyan, Md Roman, Mansor, Sarina, Hezerul, Abdul Karim
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/41594/1/Improving%20wheat%20leaf%20disease%20classification_Evaluating%20augmentation.pdf

Internet

http://umpir.ump.edu.my/id/eprint/41594/1/Improving%20wheat%20leaf%20disease%20classification_Evaluating%20augmentation.pdf

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