Artificial Intelligence Based - Oryza Sativa Leaf Ailment Recognition using DCT with Deep NN
Keywords:
Oryza Stiva, Ailment, Convolutional NN, DCT, Pre- ProcessingAbstract
India is one of the world’s second-largest producers of Oryza Sativa (Rice). Oryza Sativa feeding almost half of the world population. Human consumption accounts for 85% of total production for Oryza Sativa. Since we have enough reason to give importance to the Oryza Sativa which is getting cultivated in the field, we must combine the technical field and the agriculture field together to prevent the plant disease in the early stage. In this paper, we propose an architecture that is associated with the classificatory model for analyzing and predicting the leaf disease in Oryza Sativa by using CNN where the network accepts an image of 227 x 227 pixels and Padding is included to keep the size of the feature maps from shrinking. Along with CNN, we have combined Fast Discrete Cosine Transform which gives us a better prediction of rice disease through signal processing tool for compressing images and sounds, found in standards of JPEG format and transforming the image from spatial domain to frequency domain.
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