Rice Yield Prediction Using CNN Deep learning algorithm

Rice is one of the staple food sources of the world. Be that as it may, the creation of rice is hampered by different sorts of paddy illnesses. One of the principle illnesses of paddy is leaf infection. For the most part, it is extremely tedious and arduous for ranchers of distant regions to distinguish paddy leaf sicknesses because of inaccessibility of specialists. However specialists are accessible in certain spaces, sickness location is performed by unaided eye which causes unseemly acknowledgment here and there. A mechanized framework can limit these issues. In this paper, a programmed framework is proposed for analysis two normal paddy leaf illnesses (Leaf impact, and Bacterial curse) and pesticides or potentially composts are educated by the seriousness with respect to the sicknesses. The kind of paddy leaf illnesses is perceived by CNN. After acknowledgment, the prescient cure is proposed that can help horticulture related individuals and associations to make fitting moves against these sicknesses.