Disease Detection in Fruits Using Deep Learning


Students, Raju Hosakoti, Soma Pavan Kumar, Padmaja Jain, Assistant Professor
Dept. of ECE, BNMIT, Bangalore.


Crop cultivation plays an essential role in the agricultural field. Presently, the loss of crops is mainly due to infected crops, which reduces the production rate. It is very difficult to monitor the diseases manually. It requires a tremendous amount of work, expertise, and excessive processing time. Hence deep learning used for the detection of diseases with more accuracy. This paper aims at providing a cost-effective and real-time solution to detect fruit diseases. CNN is used for feature extraction and classification. Deep learning concepts will help to identify the diseases in fruits (Apple) with more accuracy. Hence this results in predicting the disease in an early stage so that the necessary actions to cure them can be taken immediately.