Identification of Paddy Rice Diseases Using Deep Convolutional Neural Networks

In modern digital agricultural applications, automatic identification and diagnosis of plant diseases using artificial intelligence is becoming popular widespread. Deep learning a promising tool in pattern recognition machine it can be used to identify classify paddy rice. this study, 2 different rice diseases, including blast brown spot, were investigated the district İpsala province Edirne between 2020 2021 production seasons by collecting 1569 images. These are very common important surrounding areas. Therefore, practical methods needed these two diseases. A Convolutional Neural Network (CNN) model was created applying pre-processing techniques such as rescaling, rotation, data augmentation disease The classification Google Colab, which web-based Python editor Tensorflow Keras libraries. CNN able spot with high accuracy 91.70%.