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@article{147026,
        author = {Monika and Rohit Mahajan},
        title = {COMPARATIVE ANALYSIS OF TECHNIQUES USED TO DETECT DIABETIC RETINOPATHY AT EARLY STAGE},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {3},
        pages = {105-109},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=147026},
        abstract = {Diabetic retinopathy causes the life of eye decay considerably. There are stages associated with the DR. Early detection of DR could lead to the adverse affect of DR to be minimised. Techniques have been devised to tackle and identify the problems of DR at early stage. This paper presents the comprehensive review of techniques such as machine learning and deep learning, used for the purpose of detection of DR and also performs the comparative analysis of parameters used for the same. The comparative analysis suggests that limited or no work is done towards the larger image sets corresponding to diabetic retinopathy detection. Various datasets and corresponding images for DR also plays a part that could be used to experiment the DR detection procedure. Most common phases for problem detection are also highlighted in this survey.},
        keywords = {Diabetic retinopathy, machine learning, deep learning, datasets.},
        month = {},
        }