- Agarwal, M., Singh, A., Arjaria, S., Sinha, A., & Gupta S. T. (2020). Tomato leaf disease detection using convolution neural network. Procedia Computer Science, 167, 293-301. https://doi.org/10.1016/j.procs.2020.03.225
- Ahmed, I., & Yadav, P. K. (2023). A systematic analysis of machine learning and deep learning based approaches for identifying and diagnosing plant diseases. Sustainable Operations and Computers, 4, 96-104. https://doi.org/10.1016/j.susoc.2023.03.001
- Ali, M. M., Bachik, N. A., Muhadi, N. A., Tuan Yusof, T. N., & Gomes, C. (2019). Nondestructive techniques of detecting plant diseases: A review. Physiological and Molecular Plant Pathology, 108, 101426. https://doi.org/10.1016/j.pmpp.2019.101426
- Anjna, Sood, M., & Singh, P. K. (2020). Hybrid system for detection and classification of plant disease using qualitative texture features analysis. Procedia Computer Science, 167, 1056-1065. https://doi.org/10.1016/j.procs.2020.03.404
- Balaji, V., Anushkannan, N. K., Narahari, Sujatha Canavoy, Rattan, Punam, Verma, Devvret, Awasthi, Deepak Kumar, Pandian, A. Anbarasa, Veeramanickam, M. R. M., Mulat, & Molla Bayih (2023). Deep transfer learning technique for multimodal disease classification in plant images. Contrast Media & Molecular Imaging, 5644727. https://doi.org/10.1155/2023/5644727
- Batool, A., Hyder, S. B., Rahim, A., Waheed, N., & Asghar, M.A. (2020). Classification and identification of tomato leaf disease using deep neural network. International Conference on Engineering and Emerging Technologies (ICEET). https://doi.org/10.1109/ICEET48479.2020.9048207
- Burhan, S. A., Minhas, D. S., Tariq, D. A., & Nabeel, H. M. (2020). Comparative study of deep learning algorithms for disease and pest detection in rice crops. 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). https://doi.org/10.1109/ECAI50035.2020.9223239
- Genaev, M. A., Skolotneva, E. S., Gultyaeva, E. I., Orlova, E. A., Bechtold, N. P., & Afonnikov, D. A. (2021). Image-based wheat fungi diseases identification by deep learning. Plants, 10(8), 1-21. https://doi.org/10.3390/plants10081500
- Guerrero-Ibanez, A., & Reyes-Munoz, A. (2023). Monitoring tomato leaf disease through convolutional neural networks. Electron, 12(1), 1-15. https://doi.org/10.3390/electronics12010229
- Bharali, P., Bhuyan, C., & Boruah, A. (2019). Plant Disease Detection by Leaf Image Classification Using Convolutional Neural Network. In: Gani, A., Das, P., Kharb, L., Chahal, D. (eds) Information, Communication and Computing Technology. ICICCT 2019. Communications in Computer and Information Science, vol 1025. Springer, Singapore. https://doi.org/10.1007/978-981-15-1384-8_16
- Huang, Z., Su, L., Wu, J., & Chen, Y. (2023). Rock Image Classification Based on EfficientNet and Triplet Attention Mechanism. Applied Science Letters, 13, https://doi.org/10.3390/app13053180
- Jasim, M. A., & Al-Tuwaijari, J. M. (2020). Plant leaf diseases detection and classification using image processing and deep learning techniques. International Conference on Computer Science and Software Engineering. https://doi.org/10.1109/CSASE48920.2020.9142097
- Jena, L., Sethy, P. K., & Behera, S. K. (2021). Identification of wheat grain using geometrical feature and machine learning. In: 2nd international conference for emerging technology (INCET) (pp. 1_6).
- Khan, R. U., Khan, K., Albattah, W., & Qamar, A.M. (2021). Image-based detection of plant diseases: from classical machine learning to deep learning journey. Wireless Communications and Mobile Computing, 1-13. https://doi.org/10.1155/2021/5541859
- Kirola, M., Joshi, K., Chaudhary, S., Singh, N., Anandaram, H., & Gupta, A. (2022). Plants diseases prediction framework: a imagebased system using deep learning. Proc IEEE World Conf Appl Intell Comput. https://doi.org/10.1109/AIC55036.2022.9848899
- Liu, J., & Wang, X. (2021). Plant diseases and pests detection based on deep learning: a review. Plant Methods, 17(1), 1-18. https://doi.org/10.1186/s13007-021-00722-9
- Shah, J. P., Harshadkumar, B., Prajapati, V. K., & Dabhi. (2016). A survey on detection and classification of rice plant diseases. In: IEEE international conference on current trends in advanced computing (ICCTAC).
- Upadhyay, S. K., & Kumar, A. (2022). A novel approach for rice plant diseases classification with deep convolutional neural network. International Journal of Information Technology, 14(1):185-99. https://doi.org/10.1007/s41870-021-00817-5
- Zhao, S., Peng, Y., Liu, J., & Wu, S. (2021). Tomato leaf disease diagnosis based on improved convolution neural network by attention module. Agriculture, https://doi.org/10.3390/agriculture11070651
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