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Eye Flu Recognition Using Convolutional Neural Networks
Subject area: Science,Engineering and Technology · Area of research: Machine Learning, Deep Learning
Abstract
Our research delves into the development of a sophisticated Convolutional Neural Network (CNN) for accurate identification and classification of eye flu conditions from ocular images. Leveraging state-of-the-art machine learning techniques, our study investigates the efficacy of CNNs in distinguishing between normal eye features and those indicative of flu-related ocular diseases. Through meticulous model training, validation, and testing, our approach aims to contribute to early diagnosis and effective management of eye flu conditions.
Keywords
Eye-Flu, Image Classification, CNN, AI-Powered Diagnosis
References
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How to cite this paper
@article{1705368,
author = {Omkar Singh, Manik Chandrakant Borvadkar, Ankush Sushil Singh},
title = {Eye Flu Recognition Using Convolutional Neural Networks},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {7},
number = {7},
pages = {93-98},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705368.pdf},
abstract = {Our research delves into the development of a sophisticated Convolutional Neural Network (CNN) for accurate identification and classification of eye flu conditions from ocular images. Leveraging state-of-the-art machine learning techniques, our study investigates the efficacy of CNNs in distinguishing between normal eye features and those indicative of flu-related ocular diseases. Through meticulous model training, validation, and testing, our approach aims to contribute to early diagnosis and effective management of eye flu conditions.},
keywords = {Eye-Flu, Image Classification, CNN, AI-Powered Diagnosis},
month = {January},
}