Abstract
Recognition of medicinal plants is very important to enhance plant cultivation, boost production in the medical industry as well as protect the plant species from extinction. The plant leaf is a key feature in recognizing the plant. However, standard medicinal plant leaf data sets are scarce. This chapter deals with the development of a standard data set and also the recognition of plants from their leaves using a deep learning model, as deep learning models confirmed superior recognition accuracy. With this view, here, three benchmark deep convolutional neural networks (CNN), such as InceptionV3, MobileNet, and Xception are investigated to find their respective efficacy. Extensive experiments are performed using the developed data set to recognize 11 medicinal plants from their leaf images. MobileNet deep CNN architecture confirms the optimum performance based on four evaluation metrics derived from the confusion matrix.
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Ariful Hassan, M., Sydul Islam, M., Mehedi Hasan, M., Shorif, S.B., Tarek Habib, M., Uddin, M.S. (2022). Medicinal Plant Recognition from Leaf Images Using Deep Learning. In: Uddin, M.S., Bansal, J.C. (eds) Computer Vision and Machine Learning in Agriculture, Volume 2. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-9991-7_9
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DOI: https://doi.org/10.1007/978-981-16-9991-7_9
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