Abstract
Agriculture is the mainstay of the Indian economy. Almost 70% people depend on it and share major part of the GDP. Diseases in crops are mostly on the leaves which affect on the reduction of both quality and quantity of agricultural products. Perception of human eye is not so much stronger so as to observe minute variation in the infected part of leaf. It needs lengthy process involving knowledge regarding plants as well as considerable processing time. Hence, machine learning can be used for the detection of plant diseases. Disease detection involves the steps like image acquisition, image pre-processing, image segmentation, feature extraction, and classification. In this paper, we have tried to provide solution to automatically detect and classify cotton plant leaf diseases which in turn will enhance productivity of crops.
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Shah, Z., Vania, R., Vegad, S. (2021). Disease Prediction in Plants: An Application of Machine Learning in Agriculture Sector. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_11
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DOI: https://doi.org/10.1007/978-981-15-4474-3_11
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