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Research Article
Plant Disease Detection Using Machine Learning & Image Processing
Malathi T1
Muhammed Nayif M Navab Metha2
Nourin S3
Prince Sajuvin4
Jaison Mathew John5
1234 B. Tech in Computer Science and Engineering, St. Thomas College of Engineering & Technology, Chengannur, Kerala, India 5Assistant Professor, Department of Computer Science and Engineering, St. Thomas College of Engineering & Technology, Chengannur, Kerala, India.
Published Online: May-June 2024
Pages: 10-14
Cite this article
↗ https://www.doi.org/10.59256/ijire.20240503003References
1. S. D. Khirade and A. B. Patil, “Plant Disease Detection Using Image Processing,” 2015 International conference on computing
communica tion control and automation, pp. 768–771, 2015.
2. Q. Yao, Z. Guan, Y. Zhou, J. Tang, Y. Hu and B. Yang, “Application of support vector machine for detecting rice diseases using shape
and color texture features,” 2009 international conference on engineering computation, pp. 79–83, 2009.
3. R. Deshmukh and M. Deshmukh, “Detection of paddy leaf diseases,” International Journal of Computer Applications, vol. 975, pp. 8887,
2015
4. S. Phadikar and J. Sil, “Rice Disease Identification using Pattern Recognition Techniques,” 2008 11th International Conference on
Computer and Information Technology, pp. 420–423, 2008.
5. G. Anthonys and N. Wickramarachch, “An Image Recognition System for Crop Disease Identification ofPaddy fields in Sri Lanka,” 2009
International Conference on Industrial and Information Systems (ICIIS), pp. 403–407, 2009.
6. S. Ramesh and D. vydeki “Rice Blast Disease Detection and Classification Using Machine Learning Algorithm,” 2018 2nd
International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE), pp. 255–259, 2018.
7. K. Elangovan and S. Nalini, “Plant Disease Classification Using Image Segmentation and SVM Techniques,” International Journal of
Computational Intelligence Research, vol. 13(7), pp. 1821–1828, 2017.
8. N. Mangla, P. B. Raj, S. G. Hegde and R. Pooja, “Paddy leaf disease detection using image processing and machine learning,” Int J
Innov Res Elec Electron Instrument Control Eng, vol. 7(2), pp. 97–99, 2019.
9. S. Phadikar, J. Sil and A. K. Das, “Classification of rice leaf diseases based on morphological changes,”International Journal of
Information and Electronics Engineering, vol. 2(3), pp. 460–463, 2012.
10. T. Suman and T. Dhruvakumar, “Classification of paddy leaf diseases using shape and color features,” International Journal of
Electrical and Electronics Engineers, vol. 7(1), pp. 239–250, 2015.
11. G. Athanikar and P. Badar, “Potato Leaf Diseases Detection and Classification System,” InternationalJournal of Computer Science
and Mobile Computing, vol. 5(2), pp. 76–88, 2016.
communica tion control and automation, pp. 768–771, 2015.
2. Q. Yao, Z. Guan, Y. Zhou, J. Tang, Y. Hu and B. Yang, “Application of support vector machine for detecting rice diseases using shape
and color texture features,” 2009 international conference on engineering computation, pp. 79–83, 2009.
3. R. Deshmukh and M. Deshmukh, “Detection of paddy leaf diseases,” International Journal of Computer Applications, vol. 975, pp. 8887,
2015
4. S. Phadikar and J. Sil, “Rice Disease Identification using Pattern Recognition Techniques,” 2008 11th International Conference on
Computer and Information Technology, pp. 420–423, 2008.
5. G. Anthonys and N. Wickramarachch, “An Image Recognition System for Crop Disease Identification ofPaddy fields in Sri Lanka,” 2009
International Conference on Industrial and Information Systems (ICIIS), pp. 403–407, 2009.
6. S. Ramesh and D. vydeki “Rice Blast Disease Detection and Classification Using Machine Learning Algorithm,” 2018 2nd
International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE), pp. 255–259, 2018.
7. K. Elangovan and S. Nalini, “Plant Disease Classification Using Image Segmentation and SVM Techniques,” International Journal of
Computational Intelligence Research, vol. 13(7), pp. 1821–1828, 2017.
8. N. Mangla, P. B. Raj, S. G. Hegde and R. Pooja, “Paddy leaf disease detection using image processing and machine learning,” Int J
Innov Res Elec Electron Instrument Control Eng, vol. 7(2), pp. 97–99, 2019.
9. S. Phadikar, J. Sil and A. K. Das, “Classification of rice leaf diseases based on morphological changes,”International Journal of
Information and Electronics Engineering, vol. 2(3), pp. 460–463, 2012.
10. T. Suman and T. Dhruvakumar, “Classification of paddy leaf diseases using shape and color features,” International Journal of
Electrical and Electronics Engineers, vol. 7(1), pp. 239–250, 2015.
11. G. Athanikar and P. Badar, “Potato Leaf Diseases Detection and Classification System,” InternationalJournal of Computer Science
and Mobile Computing, vol. 5(2), pp. 76–88, 2016.
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