Abstract
To meet the growing need for food in the future, precision agriculture needs to use the latest technologies and ideas. A lot of research has been done on how to keep the plants alive and how to get the most out of them. Also, it is important to know how to identify the plant species quickly so that the investigation goes in the right direction. Deep learning models are now widely used to classify things in a way that is accurate and quick. In this paper, a new method for identifying plant leaves is used and looked into. Colour image segmentation and a classification model are used together to get accurate and quick results. Colour segmentation is done by the SLIC algorithm. Inception V3 Model is implemented with minor variations. Other classification models, like support vector machines (SVM), linear regression (LR), and the K-means algorithm, are compared to the proposed method.
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Singh, R.K., Tiwari, A., Gupta, R.K. (2023). Segmentation and Classification for Plant Leaf Identification Using Deep Learning Model. In: Shukla, P.K., Mittal, H., Engelbrecht, A. (eds) Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4577-1_41
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DOI: https://doi.org/10.1007/978-981-99-4577-1_41
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