RMODCNN: A Novel Plant Disease Prediction Framework
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0892-5_45
Reference22 articles.
1. Ahmed, I., Yadav, P.K.: Plant disease detection using machine learning approaches. Expert. Syst. 40(5), e13136 (2023)
2. Bhakta, I., Phadikar, S., Majumder, K., et al.: A novel plant disease prediction model based on thermal images using modified deep convolutional neural network. Precis. Agric. 24, 23–39 (2023). https://doi.org/10.1007/s11119-022-09927-x
3. Bhatia, A., Chug, A., Singh, A.P., Singh, D.: Fractional mega trend diffusion function-based feature extraction for plant disease prediction. Int. J. Mach. Learn. Cybern. 14(1), 187–212 (2023)
4. Haridasan, A., Thomas, J., Raj, E.D.: Deep learning system for paddy plant disease detection and classification. Environ. Monit. Assess. 195(1), 120 (2023)
5. Joseph, D.S., Pawar, P.M., Pramanik, R.: Intelligent plant disease diagnosis using convolutional neural network: a review. Multimedia Tools Appl. 82(14), 21415–21481 (2023)
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