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Publication Type : Conference Paper
Publisher : 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI),
Source : 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), IEEE, Tirunelveli, India (2021)
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
Year : 2021
Abstract : Agriculture is an important sector for self-sustainability and plays a major role in a nation's economy and growth. Lack of timely identification of plant disease may result in huge loss in yield and in the economy. The objective of the research work is to support a large community of farmers particularly involved in paddy farming to understand and predict the disease affected to the crop. This research work demonstrates the robustness of classifying the paddy leaf disease using deep neural networks. Pre-processing techniques such as data augmentation and median filter have been applied to the dataset to avoid overfitting and to improve the model performance and accuracy. A model has been generated and analyzed its performance using deep learning approach. Also, the feature extracted, and preprocessed data set was fed to several models and analyzed their performance using various accuracy metrics.
Cite this Research Publication : Gowtham Kishore Indukuri, Vedha Krishna Yarasuri, and Aswathy K. Nair, “Paddy Disease Classifier using Deep learning Techniques”, in 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 2021.