Detection of Plant Diseases using Convolutional neural network & Augmented Techniques

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Abstract

In present scenario plants disease detection is a major challenge. To accomplish it we have taken Brinjal & Tomato leaves for achieving better results of diseases detection from large set of images database. In this research work, we have used Machine Learning including Edge Detection Filters & CNN. For making more accurate analysis of Disease Detection, we have applied augmented techniques to make enriched images database. In addition to this (CNN) for automatic plant disease detection has also applied. In compared to state-of-the- art detection model, computed results have shown significantly improved disease detection analysis. Using CNN based technique along with augmented approach has provided accurate disease detection results.

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Keywords

AC; ANN; CNN; ConV; DC; DCT; DL; DNN; EA; ESCA; Keras; LSR; ML; SVM; Tensorflow; WSGI