A Brief Overview of Deep Learning based Techniques for the Detection of Wheat Leaf Disease: A Recent Study

Author:

Neog Protyush Protim1,Batra Salil1,Saraswat Sudhir1,Sharma Emani Likith1,Kumar P. Pavan1,Pandey Ankit Kumar1

Affiliation:

1. Lovely Professional University,Department of Computer Science and Engineering,Phagwara,Punjab

Publisher

IEEE

Reference32 articles.

1. Leaf and spike wheat disease detection & classification using an improved deep convolutional architecture

2. Image-based wheat fungi diseases identification by deep lea;genaev;MDPI,0

3. Rice leaf diseases prediction using deep neural networks with transfer learning;krishnamorty;Environ Res,2021

4. Recognition of rice leaf diseases and wheat leaf diseases based on multi-task deep transfer learning

5. Hybrid Expert System for Wheat Diseases Diagnosis Using Fuzzy Logic, Neural Network and Bayesian Method;wijdan;University of Thi-Qar Journal of Science,0

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1. Precision Diagnosis of Wheat Powdery Mildew Using CNN and Random Forest;2024 International Conference on Emerging Smart Computing and Informatics (ESCI);2024-03-05

2. A Discriminant Ensemble Classifier Model for Hybrid Feature Vector for Efficient Detection of Diseases in Mango Leaves;2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON);2023-12-29

3. Hybrid Deep Learning for Wheat Bunt Disease Severity Assessment;2023 International Conference on Advanced Computing & Communication Technologies (ICACCTech);2023-12-23

4. Identification of Wheat Leaf Diseases Based on Deep Learning Algorithms;2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA);2023-11-22

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