Optimal deep generative adversarial network and convolutional neural network for rice leaf disease prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-02823-z.pdf
Reference38 articles.
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2. Maneesha, A., Suresh, C., Kiranmayee, B.V.: Prediction of rice plant diseases based on soil and weather conditions. In: Proceedings of International Conference on Advances in Computer Engineering and Communication Systems, pp. 155–165. Springer, Singapore (2021)
3. Vimala, S., Gladiss Merlin, N.R., Ramanathan, L., Cristin, R.: Optimal routing and deep regression neural network for rice leaf disease prediction in IoT. Int. J. Comput. Methods 18(07), 2150014 (2021)
4. Verma, T., Dubey, S.: Prediction of diseased rice plant using video processing and LSTM-simple recurrent neural network with comparative study. Multimed. Tools Appl. 80(19), 29267–29298 (2021)
5. Limkar, S., Kulkarni, S., Chinchmalatpure, P., Sharma, D., Desai, M., Angadi, S., Jadhav, P.: Classification and prediction of rice crop diseases using CNN and PNN. In: Intelligent Data Engineering and Analytics, pp. 31–40. Springer, Singapore
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