ARCHIVES

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

References

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.

Related Articles

2024

Embedding Artificial Intelligence for Personal Voice Assistant Using NLP

2024

Analysis of Pedestrian Steel Bridge subjected the Seismic Load and Wind Load using Damper at different Span

2024

Review Paper on Comparison of Asymmetric and Symmetric RCC Building with Soil Structure Interaction by Dynamic Loading

2024

BLYNK RFID and Retinal Lock Access System

2024

ML-Driven Facial Synthesis from Spoken Words Using Conditional GANs

2024

Research on smart baby cradle using sensor technology

Share Article

X
LinkedIn
Facebook
WhatsApp

Or copy link

https://theijire.com/archives/10.59256/ijire.20240503003

*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.