Author:
Nain Shubham,Mittal Neha,Singh Gajendra
Publisher
Springer Nature Singapore
Reference15 articles.
1. Patil RR, Kumar S (2022) Rice-fusion: a multimodality data fusion framework for rice disease diagnosis. IEEE Access 10:5207–5222
2. Alfred R, Obit JH, Chin CPY, Haviluddin H, Lim Y (2021) Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks. IEEE Access 9:50358–50380
3. Chen J, Chen W, Zeb A, Yang S, Zhang D (2022) Lightweight inception networks for the recognition and detection of rice plant diseases. IEEE Sens J 22(14):14628–14638
4. Upadhyay SK (2022) Deep transfer learning-based rice leaves disease diagnosis and classification model using inceptionv3. In: 2022 international conference on computational intelligence and sustainable engineering solutions (CISES). IEEE, pp 493–499
5. Ramadan STY, Sakib T, Haque MMU, Sharmin N, Rahman MM (2022) Generative adversarial network-based augmented rice leaf disease detection using deep learning. In: 2022 25th international conference on computer and information technology (ICCIT). IEEE, pp 976–981