Eye Flu Recognition Using Convolutional Neural Networks

• Author(s): Omkar Singh; Manik Chandrakant Borvadkar; Ankush Sushil Singh
• Paper ID: 1705368
• Page: 93-98
• Published Date: 08-01-2024
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 7 Issue 7 January-2024

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

Citations

IRE Journals:
Omkar Singh, Manik Chandrakant Borvadkar, Ankush Sushil Singh "Eye Flu Recognition Using Convolutional Neural Networks" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 93-98

IEEE:
Omkar Singh, Manik Chandrakant Borvadkar, Ankush Sushil Singh "Eye Flu Recognition Using Convolutional Neural Networks" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024

APA:
Omkar Singh, Manik Chandrakant Borvadkar, Ankush Sushil Singh (2024). Eye Flu Recognition Using Convolutional Neural Networks. Iconic Research And Engineering Journals, 7(7).

MLA:
Omkar Singh, Manik Chandrakant Borvadkar, Ankush Sushil Singh "Eye Flu Recognition Using Convolutional Neural Networks" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024.

BibTeX

@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}
}