Pomegranate Leaf Disease Detection Using Supervised and Unsupervised Algorithm Techniques
Author:
Affiliation:
1. Dr. A. P. J. Abdul Kalam University, Indore, Madhya Pradesh, India
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Information Systems,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/01969722.2023.2166192
Reference17 articles.
1. Design and Evaluation of a Convolutional Neural Network for Banana Leaf Diseases Classification
2. Dubey, S. R., and A. S. Jalal. 2012. Detection and classification of apple fruit diseases using complete local binary patterns. 2012 Third International Conference on Computer and Communication Technology, 346–51. IEEE.
3. Gadade, H. D., and D. K. Kirange. 2020. Tomato leaf disease diagnosis and severity measurement. 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4), 318–23, IEEE.
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1. Comparative Analysis of Transfer Learning, LeafNet, and Modified LeafNet Models for Accurate Rice Leaf Diseases Classification;IEEE Access;2024
2. Survey on Machine Learning Techniques for the Identification and Classification of Plant Leaf Diseases;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01
3. A Paradigm Shift in Pomegranate Leaf Disease Detection with Federated Learning and CNN;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06
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