Rice Crop Disease Identification and Classifier

Authors

  • Lahu Bansod V Dept. of Computer Science and Engineering,Rajiv Gandhi College of Engineering, Research and Technology, Chandrapur, India

Keywords:

plant Diese, Rice Crop,, SVM, preprocessing, Feature extractioN, wireless sensor, k-mean

Abstract

many papers have been referred, covering the work on rice plant diseases and other different plants and fruits, and present a survey of few papers based on important criteria. These criteria include size of image dataset, no. of classes (diseases), preprocessing, segmentation techniques, types of classifiers, accuracy of classifiers etc. Utilize this survey and study to propose a work on detection and classification of rice crop diseases

References

[1] R.Rajmohan, M.Pajany,R.Rajesh,D.Raghu Raman, U. Prabu, “ SMART PADDY CROP DISEASE IDENTIFICATION AND MANAGEMENT USING DEEP CONVOLUTION NEURAL NETWORK AND SVM CLASSIFIER” International Journal of Pure and Applied Mathematics Volume 118 No. 15 2018, 255-264

[2] JITESH P. SHAH, HARSHADKUMAR B. PRAJAPATI, VIPUL K. DABHI,”A SURVEY ON DETECTION AND CLASSIFICATIOPN OF RICE PLANT DISEASES” 2016 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC) 15 September 2016

[3] Malti K. Singh, Subrat Chetia,”Detection and Classification of Plant Leaf Diseases in Image Processing using MATLAB”, International Journal of Life Sciences Research ISSN 2348-3148 (online) Vol. 5, Issue 4, pp: (120-124), Month: October - December 2017

[4] Sachin Khirad, A. B. Patil,” Plant Disease Detection Using Image Processing”, IEEE ICCUBEA.2015.153

[5] DETECTION & PREDICTION OF PESTS/DISEASES USING DEEP LEARNING, from website: https://innovate.mygov.in/wp-content/uploads/2018/09/mygov1536109003113172.pdf

[6] 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," in Engineering Computation, 2009. ICEC`09. International Conference on IEEE, 2009, pp. 79{83.

[7] G. Anthonys and N. Wickramarachchi, An image recognition system for crop disease identification of paddy fields in sri lanka," in 2009 International Conference on Industrial and Information Systems (ICIIS). IEEE, 2009, pp. 403{407.

[8] AI and IoT methods for plant disease detection in Myanmar from website: https://www.researchgate.net/publication/326988635_IoT_and_AI_methods_for_plant_disease_detection_in_Myanmar.

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Published

2025-11-25

How to Cite

[1]
V. Lahu Bansod, “Rice Crop Disease Identification and Classifier”, Int. J. Comp. Sci. Eng., vol. 7, no. 11, pp. 45–48, Nov. 2025.

Issue

Vol. 7 No. 11 (2019): IJCSE Special Issue May Edition

Section

Survey Article

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