Author:
Dubey Ratnesh Kumar,Choubey Dilip Kumar
Publisher
Springer Nature Singapore
Reference36 articles.
1. Elmitwally NS, Tariq M, Khan MA, Ahmad M, Abbas S, Alotaibi FM (2022) Rice leaves disease diagnose empowered with transfer learning. Comput Syst Sci Eng. https://doi.org/10.32604/csse.2022.022017
2. Bakar MA, Abdullah AH, Rahim NA, Yazid H, Misman SN, Masnan MJ (2018) Rice leaf blast disease detection using multi-level colour image thresholding. J Telecommun Electron Comput Eng 10(1–15):1–6
3. Kim Y, Roh JH, Kim HY (2018) Early forecasting of rice blast disease using long short-term memory recurrent neural networks. Sustainability. https://doi.org/10.3390/su10010034
4. Liu LW, Hsieh SH, Lin SJ, Wang YM, Lin WS (2021) Rice blast (Magnaporthe oryzae) occurrence prediction and the key factor sensitivity analysis by machine learning. Agronomy. https://doi.org/10.3390/agronomy11040771
5. Sime HD, Mbong GA, Malla DK, Suh C (2017) Effect of different doses of NPK fertilizer on the infection coefficient of rice (Orysa sativa L.) blast in Ndop, North West of Cameroon. Agron Africaine