A Novel Approach for Detection of Ocular Diseases using Deep Learning Concepts

The Biggest demanding situations for the attention professional is the identification and prognosis of the eye diseases from the given retinal pictures. The process of figuring out the form of eye sicknesses is hard and takes huge amount of time. Therefore, a computer advanced automated eye ailment detection system is needed for the detection of numerous eye diseases utilizing retinal photographs. As the imaging capabilities of deep studying algorithms improve, such systems may eventually be found out. In this paper, we use Deep Learning Concepts and CNN algorithm. The system is split into 3 classes, preprocessing, segmentation, and categorization. There are various modules used in this venture which consists of photograph enhancement and segmentation and many others for the system of eye tumour detection. The images from the dataset are first preprocessed and then the images are segmented and formed the trained dataset and then the classification process is done using CNN algorithm and the desired result is obtained. For this paper, we have developed an image classification algorithm. Each class represents a different eye disease.