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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Detection Of Eye Conditions using Deep Learning |
| Authors Name: | Mohammed Shimnaz E K , Mrs. Jyothi Prasad , Mayur Jalesh , Mohammed Danish A V , Muhammed Hashir Zubair |
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| Author Reg. ID: |
IJNRD_195804
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| Published Paper Id: | IJNRD2305474 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Eye Disease is a frequent health issue that can cause partial or total visual loss. Early diagnosis is essential for eye disease to be effectively treated and managed .Deep learning has become a potent tool for the detection and diagnosis of numerous medical disorders, including eye diseases , in recent years. Convolutional Neural Network(CNN) is a deep learning technique that is often used for image analysis and pattern recognition. In this approach, we use a CNN based method for classifying various eye diseases. The suggested method extracts features from eye images and categorises them using CNN.A dataset of eye images was collected, including images of healthy eyes as well as diseased eyes which are Cataracts, Glaucoma, Bulging eyes, Uveitis, and Crossed Eyes. The dataset underwent preprocessing to normalise the images and get rid of any noise. The training and testing sets were then created from the preprocessed dataset. A CNN model is trained using the pre-processed pictures, and it is then tuned using fine-tuning methods. The proposed approach will achieve high accuracy in detecting eye conditions. The results indicate that this approach can be a valuable tool in the early detection and diagnosis of eye conditions, which can improve the outcomes of treatment and prevent vision loss. |
| Keywords: | Convolutional neural networks , Cateract, Dataset , preprocessing. |
| Cite Article: | "Detection Of Eye Conditions using Deep Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.e589-e593, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305474.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305474 Registration ID: 195804 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: e589-e593 Country: KANNUR, KERALA, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305474 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305474 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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