Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
This paper showcases a facial emotion recognition system leveraging Convolutional Neural Networks (CNNs) and machine learning. The model, trained using Keras and TensorFlow on 48x48 grayscale facial images, accurately predicts emotions. Integrating OpenCV, it tracks and detects faces in live video feeds, interpreting facial expressions to identify emotions like anger, happiness, and sadness. The system generates emojis reflecting these emotions, presented via a Tkinter-based GUI. Notably, upcoming enhancements aim to refine emoji generation by considering gender differences, introducing nuanced representations for males and females. Moreover, a focus on advancing object detection capabilities intends to identify glasses or spectacles, adding further depth to emoji portrayal. Future aspirations involve transforming the system into a mobile application, enabling real-time emotion capture, and providing insights into mental health via emojis. This project amalgamates machine learning, computer vision, and user interface design, aiming to enhance accuracy, personalization, and real-world applicability for diverse user engagement and mental health monitoring.
"Emo Face - Emotions to Emoji Avatars Using CNN", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 12, page no.539 - 547, December-2023, Available :http://www.ijrti.org/papers/IJRTI2312076.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator