an identification of plant leaf disease detection using hybrid ann and knn

Publication Type: Edited Book

Book Name: Futuristic Trends in IOT V3B8
Authors: Sai Srinivas Vellela, Dr K Kiran Kumar, Dr .M Venkateswara Rao, Venkateswara Reddy B, Khader Basha Sk, Roja D
Keywords: Plant diseases, Image analysis, feature extraction, Artificial Neural Networks (ANN) and Convolutional Neural Network (CNN).
Area/Stream: SENSORS, IoT & SMART SYSTEMS / Other /
Published in: IIP Series
Volume: 3, Month:May,Year:2023
Page No.: 149-158
e-ISBN: 978-93-6252-960-2
DOI: https://www.doi.org/10.58532/V3BAIO8P5CH4

Abstract:

Plant diseases are a regular cause of low yields and lessen the income for farmers. Detecting plant diseases is an important task in the agribusiness sector because plant diseases are common. To detect diseases in the leaves, it is necessary to constantly monitor the plants. However, manual detecting of diseases consumes a more period and effort. Hence, it is better to have an automated system. This analysis describes identification of plant leaf disease detection using hybrid Artificial Neural Networks (ANN) and Convolutional Neural Network (CNN). The characteristics are detected for the non-infected and infected regions of the leaf. The complete data set containing of 300 images and classified for training and testing. These images are executed with the described technique as well as it is classified as infected or non-infected. Hybridized model achieves 98% of Accuracy, 97% of Precision and 96% of Recall. Observational output shows that plant infections will be classified exactly.

Cite this: Sai Srinivas Vellela, Dr K Kiran Kumar, Dr .M Venkateswara Rao, Venkateswara Reddy B, Khader Basha Sk, Roja D, AN IDENTIFICATION OF PLANT LEAF DISEASE DETECTION USING HYBRID ANN AND KNN, In: Futuristic Trends in IOT V3B8, IIP Series, Volume 3, May, 2023, pp. 149-158, Iterative International Publishers IIP, E-ISBN: 978-93-6252-960-2, DOI: https://www.doi.org/10.58532/V3BAIO8P5CH4

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