Facial Emotion Recognition using OpenCV and Deepface

Facial Emotion Recognition on FER2013 Dataset Using a Convolutional Neural Network

A facial emotion recognition program implemented in Python using TensorFlow, Keras and OpenCV and trained on the FER2013 dataset with FERPlus' labels.

Facial Expression Recognition (FER) for Mental Health Detection applies AI models like Swin Transformer, CNN, and ViT for detecting emotions linked to anxiety, depression, PTSD, and OCD. It focuses on AI for mental health, emotion detection using OpenCV Python, and real-time applications in healthcare and HR systems.

This Repo consist code for transfer learning for facial emotion detection via valence and arousal levels. We used pretrained weights from VGG-16 net and apply on that features deep neural network and lstm model in pytorch. We tested our model on Aff-wild net dataset.

I have used FER2013 dataset and try to build the Facial emotion recognition using Keras

Method for facial emotion recognition compitition of Xunfei and Datawhale .

🔭 Real-time Streamlit Facial Emotion Recognition web application to monitor student's mood in a classroom

Emotion (Context + Facial) recognition in the wild using ConvNets (EfficientNet, ResNet, ResNext)

Facial expression recognition using keras model

This repository is devoted to the development of the facial emotion recognition (FER) system as a final bachelor project at the TU/e. Realised by Blazej Manczak. Supervisors: Dr. Laura Astola (Accenture) and Dr. Vlado Menkovski (TU/e)

This project is a basic emotion recognition system that combines OpenAI's GPT API and a deep learning model trained on the FER2013 dataset. It detects facial emotions in real-time from a webcam feed and generates AI responses based on the user's emotion. The project is implemented using TensorFlow, OpenCV, and OpenAI's API

I have used FER2013 dataset and try to build the Facial emotion recognition using TensorFlow

personalized facial expression recognition

CNN (Convolutional neural network)-based facial expression recognition model (with pretrained weights) implemented with Pytorch

Models and tools for recognizing 16 emotions from smartphone videos, with pretrained SVM and GRU-Attention models based on the FER-STREs-WoZ dataset.

a project which uses machine learning techniques to analyse the emotion of a person in real time using a camera module.

Facial emotion recognition by using convolutional neural network (CNN)

Using dlib, OpenCV, and Python, to detect in real time how to open/closed eyes,mouth, position of the head, and the emotion

Ad-Corre: Adaptive Correlation-Based Loss for Facial Expression Recognition in the Wild