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Bio Vision: AI-based Secure and Accurate Visual Expression Analysis System
Subject area: Science,Engineering and Technology · Area of research: Deep Learning for Facial Expression Recognition
Abstract
This paper presents Bio Vision, an advanced AI-based system for facial expression analysis using Convolutional Neural Networks (CNN). The proposed system aims to achieve secure, reliable, and real-time detection of human emotions through visual input. The model is trained using grayscale facial images and achieves high accuracy in identifying seven emotional states ? angry, disgust, fear, happy, neutral, sad, and surprise. This study demonstrates how deep learning can be utilized to enhance human-computer interaction (HCI) and emotion-aware systems.
Keywords
Artificial Intelligence, CNN, Facial Expression Recognition, Emotion Detection, Deep Learning.
References
[1] I. Goodfellow et al., 'Deep Learning,' MIT Press, 2016.
[2] S. Li and W. Deng, 'Deep Facial Expression Recognition: A Survey,' IEEE Transactions on Advanced Computing, 2020.
[3] K. Simonyan and A. Zisserman, 'Very Deep Convolutional Networks for Large-Scale Image Recognition,' arXiv:1409.1556, 2014.
How to cite this paper
@article{1711713,
author = {Avnish Kumar, Keshav Kumar, Dilip Kumar, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri},
title = {Bio Vision: AI-based Secure and Accurate Visual Expression Analysis System},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {351-351},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1711713.pdf},
abstract = {This paper presents Bio Vision, an advanced AI-based system for facial expression analysis using Convolutional Neural Networks (CNN). The proposed system aims to achieve secure, reliable, and real-time detection of human emotions through visual input. The model is trained using grayscale facial images and achieves high accuracy in identifying seven emotional states ? angry, disgust, fear, happy, neutral, sad, and surprise. This study demonstrates how deep learning can be utilized to enhance human-computer interaction (HCI) and emotion-aware systems.},
keywords = {Artificial Intelligence, CNN, Facial Expression Recognition, Emotion Detection, Deep Learning.},
month = {November},
doi = {https://doi.org/10.64388/IREV9I5-1711713}
}