Abstract
Agriculture plays a substantial role in any country’s growth. But, the unfortunate fact is that many plants are wizened due to the inexpert approach towards their growth. Plant diseases affect the crop’s growth which needs to be detected at an early stage using some automated monitoring technique so that the loss can be avoided. One such technique that can help in the early detection of disease in plants is deep learning. Deep learning is a subset of machine learning. The deep learning model used in this paper is Convolutional Neural Networks. The motivation behind doing this project is to help the farmers in increasing their income as this system will help in the early detection of plant diseases and will also act as a milestone in taking traditional farming to smart farming. This will eventually lead to increased crop yield and reduced crop loss. This approach will also be beneficial to the pesticide companies as they can design their pest controls accordingly.
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Prashar, N., Sangal, A.L. (2022). Plant Disease Detection Using Deep Learning (Convolutional Neural Networks). In: Chen, J.IZ., Tavares, J.M.R.S., Iliyasu, A.M., Du, KL. (eds) Second International Conference on Image Processing and Capsule Networks. ICIPCN 2021. Lecture Notes in Networks and Systems, vol 300. Springer, Cham. https://doi.org/10.1007/978-3-030-84760-9_54
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DOI: https://doi.org/10.1007/978-3-030-84760-9_54
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