1. Abdel-Basset, M., Mohamed, R., Hezam, I. M., Sallam, K. M., Alshamrani, A. M., & Hameed, I. A. (2023). A novel binary Kepler optimization algorithm for 0–1 knapsack problems: Methods and applications. Alexandria Engineering Journal, 82, 358–376.
2. Aggarwal, S., Suchithra, M., Chandramouli, N., Sarada, M., Verma, A., Vetrithangam, D., Pant, B., & AmbachewAdugna, B. (2022). Rice disease detection using artificial intelligence and machine learning techniques to improvise agro-business. Scientific Programming, 2022(2), 1–13.
3. Agrawal, M. M., & Agrawal, S. (2020). Rice plant diseases detection & classification using deep learning models: A systematic review. Journal of Critical Reviews, 7(11), 4376–4390.
4. Bari, B. S., Islam, M. N., Rashid, M., Hasan, M. J., Razman, M. A. M., Musa, R. M., Ab Nasir, A. F., & Majeed, A. P. A. (2021). A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework. PeerJ Computer Science, 7, e432.
5. Burhan, S.A., Minhas, S., Tariq, A., & Hassan, M.N. (2020) June. Comparative study of deep learning algorithms for disease and pest detection in rice crops. In 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), 1–5. IEEE.