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Probabilistic Neural Network for Automatic Detection of Plant Diseases Using DT-CWT and K-Means Feature Extraction
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| Author:
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V. SRIYA, DR.T. MANORANJITHAM, R. ISHWARYA
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| Abstract:
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The proposed system will be used to automatically detect leaf characteristics and classify the diseased test images according to features extracted. In modern day agricultural research, automatically detecting and classifying leaf patterns and characteristics is cardinal in large scale crop plantations. They are used to simultaneously detect symptoms of diseases in plants and provide results, immediately after their appearance. The decision-making system that is proposed in this paper will use image content characterization and a probabilistic neural network which uses a supervised classifier. Image processing techniques for this kind of decision analysis involves preprocessing, feature extraction and classification stage.
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| Keyword:
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K-Means, Probabilistic Neural Network, Radial Basis Function, DT-CWT, Plant Diseases, Image Classification.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.01.219
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| Download:
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