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Cotton Leaf Disease Detection Using Instance Segmentation

Cotton Leaf Disease Detection Using Instance Segmentation

Prashant Udawant, Pravin Srinath
Copyright: © 2022 |Volume: 24 |Issue: 4 |Pages: 10
ISSN: 1548-7717|EISSN: 1548-7725|EISBN13: 9781799878230|DOI: 10.4018/JCIT.296721
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MLA

Udawant, Prashant, and Pravin Srinath. "Cotton Leaf Disease Detection Using Instance Segmentation." JCIT vol.24, no.4 2022: pp.1-10. http://doi.org/10.4018/JCIT.296721

APA

Udawant, P. & Srinath, P. (2022). Cotton Leaf Disease Detection Using Instance Segmentation. Journal of Cases on Information Technology (JCIT), 24(4), 1-10. http://doi.org/10.4018/JCIT.296721

Chicago

Udawant, Prashant, and Pravin Srinath. "Cotton Leaf Disease Detection Using Instance Segmentation," Journal of Cases on Information Technology (JCIT) 24, no.4: 1-10. http://doi.org/10.4018/JCIT.296721

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Abstract

Cotton is one of the most important cash and fiber crops in India. Agricultural machine learning plays a very important role in this agricultural industry. In this paper, the use of an object detection algorithm namely Mask RCNN along with transfer learning is experimented to find out if it is a fit algorithm to detect cotton leaf diseases in practical situations. The model training accuracy is found as 94 % whereas total loss value is continuously decreasing as number of optimize iterations are increasing.