Abstract
Medicinal plant identification is a challenging but very useful task in computer vision (CV). Deep convolutional neural network (CNN) is promisingly used in plant identification as experimentally proved in this paper. It presents a new setup to capture efficiently plant leaves and are used for classification. Secondly, \(l\alpha \beta \) color space is used to improve the performance of CNN in plant species recognition. For this experiment, two different types of datasets are used showing the robustness of our approach.
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Prasad, S., Singh, P.P. (2017). Vision System for Medicinal Plant Leaf Acquisition and Analysis. In: Contractor, D., Telang, A. (eds) Applications of Cognitive Computing Systems and IBM Watson . Springer, Singapore. https://doi.org/10.1007/978-981-10-6418-0_5
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