[1] V. Singh, N. Sharma, S. Singh, “A review of imaging techniques for plant disease detection” Artificial Intelligence in Agriculture, vol. 4, pp. 229-242, 2020, doi: 10.1016/j.aiia.2020.10.002.
[2] A. Khakimov, I. Salakhutdinov, A. Omolikov, S. Utaganov, “Traditional and current-prospective methods of agricultural plant diseases detection: A review” in Conf. Earth and Environmental Science, 2022, doi: 10.1088/1755-1315/951/1/012002.
[3] P. Moghadam, D. Ward, E. Goan, S. Jayawardena, P. Sikka, E. Hernandez, “ Plant Disease Detection Using Hyperspectral Imaging” in Conf Digital Image Computing: Techniques and Applications (DICTA), pp.1-8, 2017, doi: 10.1109/DICTA.2017.8227476
[4] D. Albashish, M. Braik, S. Bani-Ahmad, “Detection and Classification of Leaf Diseases using K-means-based Segmentation and Neural-networks-based Classification” Information Technology Journal, vol.10, 2011, doi: 10.3923/itj.2011.267.275.
[5] S. Madiwalar, M. Wyawahare, “Plant disease identification: A comparative study” in Conf 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI), Pune, India, 2017, pp.13-18, doi: 10.1109/ICDMAI.2017.8073478.
[6] M. Li, et al., “High-Performance Plant Pest and Disease Detection Based on Model Ensemble with Inception Module and Cluster Algorithm”, Plants (Basel), vol.12, 2023, doi: 10.3390/plants12010200.
[7] حمید حسنپور، سکینه اسدی امیری، "مفاهیم جامع پردازش تصویر دیجیتال بههمراه پیادهسازی الگوریتمها با متلب"، انتشارات دانشگاه صنعتی شاهرود، 1395
[8] P. Kulkarni, A. Karwande, T. Kolhe, S. Kamble, A. Joshi, M. Wyawahare, “Plant Disease Detection Using Image Processing and Machine Learning,” Nov 2021, doi:10.48550/arXiv.2106.10698.
[9] S. Mohanty, D. Hughes, M. Salathe, “Using Deep Learning for Image-Based Plant Disease Detection,” Frontiers in Plant Science, vol.7, Sep 2016, doi: 10.3389/fpls.2016.01419.
[10] D.M. Sharath, A. Akhilesh, S.A. Kumar, M.G. Rohan, C. Prathap, “Image based Plant Disease Detection in Pomegranate Plant for Bacterial Blight,” in Conf International Conference on Communication and Signal Processing, Chennai, India, 2019, doi: 10.1109/ICCSP.2019.8698007
[11] V. Suresh, M. Krishnan, M. Hemavarthini, D. Jayanthan, “Plant Disease Detection using Image Processing,” International Journal of Engineering Research, vol.9 Mar 2020, doi: 10.17577/IJERTV9IS030114.
[12] N. Ibraheem, M. Hasan, R.Z. Khan, P. Mishra, “Understanding Color Models: A Review,” ARPN Journal of Science and Technology, vol.2, Jan 2012,
[13] J. Miao, L. Niu, “A Survey on Feature Selection,” Procedia Computer Science. Vol.91, pp.919-926, Jul 2016, doi: 10.1016/j.procs.2016.07.111.
[14] J. Ali, R. Khan, N. Ahmad, I. Maqsood, “Random Forests and Decision Trees,” International Journal of Computer Science Issues(IJCSI), vol.9, Sep 2012.
[15] J. Cervantes, F. Garcia-Lamont, L. Rodríguez-Mazahua, A. Lopez, “A comprehensive survey on support vector machine classification: Applications, challenges and trends,” Neurocomputing, vol.408, pp. 189-215, Sep 2020, doi: 10.1016/j.neucom.2019.10.118.
[16] S. BHATTARAI, (2018), New Plant Diseases Dataset. PlantVillage, [online] Available: https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset?resource=download.
[17] S. Mohanty, (2016), PlantVillage Dataset, Available:https://github.com/spMohanty/PlantVillage-Dataset.
[18] G. Shrestha, Deepsikha, M. Das, N. Dey, “Plant Disease Detection Using CNN,” in Conf IEEE Applied Signal Processing Conference (ASPCON), Kolkata, India, 2020, pp.109-113, doi:10.1109/ASPCON49795.2020.9276722
[19] R. Mahum, H. Munir, Z. Mughal, “A novel framework for potato leaf disease detection using an efficient deep learning model,” Human and Ecological Risk Assessment: An International Journal, vol.29, pp.303-326, Feb 2023, doi: 10.1080/10807039.2022.2064814
[20] A.I. Khan, S.M.K Quadri, S. Banday, J.L. Shah “ Deep diagnosis: A real-time apple leaf disease detection system based on deep learning,” Computers and Electronics in Agriculture Journal, vol.198, July 2022, doi: https://doi.org/10.1016/j.compag.2022.107093
[21] X.Gong, S.Zhang “ An Analysis of Plant Diseases Identification Based on Deep Learning Methods,” The Plant Pathology Journal, vol.39(4), 319-334, Aug 2023, doi: https://doi.org/10.5423/PPJ.OA.02.2023.0034
[22] M.Jung, J.S.Song, A.Shin, B.Choi, S.Go “ Construction of deep learning based disease detection model in plants,” Scientific Reports Journal, vol.13, May 2023, doi: https://doi.org/10.5423/PPJ.OA.02.2023.0034
[23] S.U.Rahman, F.Alam, N.Ahmad, S.Arshad “ Image processing based system for the detection, identification and treatment of tomato leaf diseases,” Multimedia Tools and Applications Journal, vol.82, pp.9431-9445, Sep 2022, doi: https://doi.org/10.1007/s11042-022-13715-0
[24] A.Haridasan, J.Thomas, E.D.Raj “ Deep learning system for paddy plant disease detection and classification,” Environmental Monitoring and Assessment Journal, vol.195, May 2022, doi: https://doi.org/10.1007/s10661-022-10656-x
[25] M.M.Khalid, O.Karan “ Deep Learning for Plant Disease Detection,” International Journal of Mathematics, Statistics, and Computer Science, vol.2, pp.75-84, Nov 2023, doi: https://doi.org/10.59543/ijmscs.v2i.834
[26] I.Ahmed, P.K.Yadav “ Plant disease detection using machine learning approaches,” Expert Systems Journal, vol.40, Oct 2022, doi: https://doi.org/10.1111/exsy.13136
[27] M.Soeb, M.Jubayer, T.Tarin, et al “ Tea leaf disease detection and identification based on YOLOv7 (YOLO T),” Scientific Reports Journal, vol.13, Apr 2023, doi: https://doi.org/10.1038/s41598-023-33270-4