Prediction of crop disease using Rank Regressive Learning and Proaftn Fuzzy Classification models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08357-9.pdf
Reference20 articles.
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2. Ahmed N, Khan MA, Khan NA, Ali MA (2015) Prediction of potato late blight disease based upon environmental factors in Faisalabad. Pakistan J Plant Pathol Microbiol S. https://doi.org/10.4172/2157-7471.S3-008
3. Bhatia A, Chug A, Prakash Singh A (2020) Application of extreme learning machine in plant disease prediction for highly imbalanced dataset. J Stat Manag Syst 23(6):1059–1068
4. Dahiya S, Gulati T, Gupta D (2022) Performance analysis of deep learning architectures for plant leaves disease detection. Meas Sens 24:100581. https://doi.org/10.1016/J.MEASEN.2022.100581
5. de Oliveira Aparecido LE, de Souza Rolim G, da Silva Cabral De Moraes JR, Costa CTS, de Souza PS (2020) Machine learning algorithms for forecasting the incidence of Coffea arabica pests and diseases. Int J Biometeorol 64:671–688
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1. An Optimized Deep Learning Technique for Enhance Disease Identification in Tomato Leaf to Promote Sustainable Agriculture;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20
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