Year: 2025
Type: article
Abstract: - In recent years, the intersection of artificial intelligence and human-computer interaction has gained significant attention, particularly in the realm of emotion detection. This paper presents a novel approach to real-time emotion detection using Convolutional Neural Networks (CNN) and OpenCV for facial recognition. By leveraging advanced image processing techniques and deep learning algorithms, our system can accurately identify and classify human emotions based on facial expressions in real-time. This capability has profound implications for various applications, including mental health monitoring, customer service, and interactive gaming. We detail the methodology, implementation, and evaluation of our system, demonstrating its effectiveness and potential for future developments. Keywords : Facial Expression Recognition, Convolutional Neural Networks, Deep Learning, Emoji Generation, Human-Computer Interaction, Real-time Analysis, Sentiment Detection, Machine Learning, Mental Health Analysis, Virtual Learning.
DOI: 10.55041/ijsrem47928
Authors: author, Mr. S.R.Sridhar
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4410408968