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Neuro-kNN classification system for detecting fungal disease found on vegetable crops using local binary patterns CIGR Journal
yakkundimath, rajesh siddaramayya.
This paper describes the behavior of classifiers for identification and classification of fungal disease symptoms found on vegetable crops. Symptoms of fungal disease, namely, anthracnose, powdery mildew, rust, downey mildew, early blight, and late blight found on specific type of vegetable crop are considered for recognition and classification. The way the disease analysis is done considering both sides (front and back portions) of the leaves has been addressed. The analysis of the fungal disease present on the leaves of vegetable crops is detected in the early stage before it damages the whole leaf and subsequently the plant. The Local Binary Patterns(LBP) extracted from disease affected leaves are used as input to the classifiers. An integrated...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Computer science; Agriculture engineering Fungal disease; Vegetable crops; Local Binary Patterns; Artificial Neural Network; K-Nearest Neighbor.
Ano: 2014 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2965
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