Plant diseases function a serious threat to food supply. Paddy is one amongst the most importantcultivated crops in India which is full of various diseases at various stages of its cultivation. it's very difficultfor the farmers to manually identify these diseases accurately with their limited knowledge. The Paddy leaf suffers from several bacterial, viral, or fungal diseases and these diseases reduce Paddy production significantly. To sustain Paddy demand for an enormous population globally, the popularity of Paddy leafdiseases is crucially important[6]. However, recognition of Paddy plant disease is proscribed to the imagebackgrounds and image capture conditions. The convolutional neural network (CNN) based model may be a hot research topic within the field of Paddy plantdisease recognition[4]. But the prevailing CNN-based models call recognition rates severely on independent dataset and are limited to the educational of enormous scalenetwork parameters. The projected system helps in detection of crop diseases and provides remedies whichcould defend in contradiction of the crop infection. the knowledge from the net is split and also the totally different crop disease types are known and are relabeled in order that we are able to create accurate information hen get a sample database which consists of varied crop diseases which is able to help in identifying the accuracy levels of the applying .the effectiveness and superiority of our approach compared to the state-of-the-art CNN-based Paddy plant disease recognition model. Keyword: Image Recognition, plant disease prediction, CNN.

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