Abstract
Emoticons have become a ubiquitous part of online communication, but their limitations hinder the expression of nuanced emotions. This project proposes "Emojify," a system that leverages deep learning for real-time emotion recognition through video input. By employing techniques like pre-processing, face detection, and Convolutional Neural Networks (CNNs), Emojify analyzes facial expressions and generates corresponding emojis. This approach goes beyond traditional emoticons, dynamically reflecting emotional intent and enriching virtual communication. The project explores the potential for entertainment applications and user-friendly emoji creation tools with encryption and decryption methods. Emojify holds promise for bridging the emotional gap in virtual interactions, fostering a more expressive and engaging online experience.
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