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ABSTRACT
Traditional farming is going out of date nowadays. Technologies are being introduced in the farming sector for the past decade and in recent years it is seenthat the participation of deep learning and machine learning is playing an integral role in solving traditional problems. The introduction of new technology has increased the productivity of farmers and also increased the yields and quality of the crops too. Plant diseases are a serious concern for the consumers and the farmers too. It does not only carry some harmful bacteria within itself however it compromises the yield of the crops too. The identification of such plant diseases has been a continuous problem for cultivators and researchers. Deep learning-enabled developments in the field of computer vision have paved the path for computer- assisted plant disease diagnosis. Deep Learning has achieved great success in the categorization of a number of plant diseases by exploiting its ability to recognize objects with the help of convolutional neural networks. Various deep learning algorithm like AlexNet and LeNet-5 is applied on a publicly available dataset (plantvillage dataset) so that the neural network can capture the various features of a specific disease and diagnose it accordingly using a human-like decision making skill.
