Abstract
In India, more than 80% of agrarian crops are produced by smallholder farmers. The reports point that almost half the yield loss is mainly due to pests and diseases. Unlike pests, diseases are more difficult to detect and treat. Numerous studies and researches have been put forward to identify the behaviour of different diseases. Traditionally, farmers use naked eye observation for detecting disease but one of the areas considered today is processing the images with machine learning concepts to assist the farmers technologically. This paper presents an image processing strategy to classify sort of disease in a cucumber plant and gives a severity measure of malady spots in the cucumber leaf caught under real field condition.
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Krishnakumar, A., Narayanan, A. (2019). A System for Plant Disease Classification and Severity Estimation Using Machine Learning Techniques. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_45
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DOI: https://doi.org/10.1007/978-3-030-00665-5_45
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