# Real Time Emotion Analysis Using Deep Learning for Education, Entertainment, and Beyond

arXiv: https://arxiv.org/abs/2407.04560 · HTML: https://mlsanity.com/paper/2407.04560/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 27 references that are in the map.
- First posted on arXiv 5 Jul 2024.

## Builds on (most cited first, 4 of 4)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [A Tutorial on Principal Component Analysis](https://mlsanity.com/paper/1404.1100/) (2014)

## Abstract (arXiv)

The significance of emotion detection is increasing in education, entertainment, and various other domains. We are developing a system that can identify and transform facial expressions into emojis to provide immediate feedback.The project consists of two components. Initially, we will employ sophisticated image processing techniques and neural networks to construct a deep learning model capable of precisely categorising facial expressions. Next, we will develop a basic application that records live video using the camera on your device. The app will utilise a sophisticated model to promptly analyse facial expressions and promptly exhibit corresponding emojis.Our objective is to develop a dynamic tool that integrates deep learning and real-time video processing for the purposes of online education, virtual events, gaming, and enhancing user experience. This tool enhances interactions and introduces novel emotional intelligence technologies.