Abstract
Food is the main resource for humans; securing and taking care of the plants are the number one priority. Raises in crop leaf disease are becoming a major problem in agriculture. Taking care of the disease in the early stage will prevent the disease from spreading between plants. Modern technology will be the way for the detection of crop leaf disease. The deep learning technology made it easier to detection of crop leaf diseases. The dataset used for training is publicly available. The trained model can classify up to 15 diseases. The training accuracy reached 97.35% which is more than enough to detect disease accurately. The proposed project can detect crop leaf disease with higher accuracy which can be utilized to detect the disease in the real world.
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Bhoomika, S.S., Poornima, K.M. (2023). Plant Leaf Disease Detection and Classification Using Deep Learning Technique. In: Bhateja, V., Sunitha, K.V.N., Chen, YW., Zhang, YD. (eds) Intelligent System Design. Lecture Notes in Networks and Systems, vol 494. Springer, Singapore. https://doi.org/10.1007/978-981-19-4863-3_7
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DOI: https://doi.org/10.1007/978-981-19-4863-3_7
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