FER model uses Convolutional Neural Network algorithm trained on FER2013 dataset to recognize five universal emotions of the Facial Action Coding System. It can detect multiple faces with exceptionally outstanding results. (IEEE Published)

A human emotion recognition based learning assistant. HACKOH/IO - 2019

The purpose of this project was to simply test a CNN model on a competition FER2013 dataset.

This GitHub repository hosts a Facial Emotion Recognition project that utilizes Convolutional Neural Networks (CNNs) to detect emotions from facial expressions in real-time. Built with Python, TensorFlow, Keras, and OpenCV, the project includes scripts for training the emotion detection model using the FER 2013 dataset and testing it with live webc

Tackling facial emotion recognition (FER) tasks using DCNNs, VGG16 and Inception-V3 models

An academic research project for comparative analysis of deep learning models in facial emotion recognition.

An emotion detection CNN-based model that can detect emotions from images in real-time

A ready-to-use Facial Expression Recognition model using MobileNet on augmented FER2013 dataset. Val accuracy > 89%

Emotion Detection using deep unbaised CNN!!

Product Market Analysis is a software that allows Companies to receive reviews on their products from Beta Testers by using Deep Learning to detect facial expressions.

A website that performs facial emotion analysis on uploaded images using AI!

A Deep Learning model deployed with FastAPI recognizes emotions using facial expression.

A implementation for facial expression recognition on fer2013 dataset using Residual Masking Network architecture

It intergrate a custom built pure cnn based facial emotion recogtion model with accuracy of 64% in a web that implements technology like webRTC and asunchronous js.

The goal of facial expression detection is to accurately identify the emotions expressed by a person's face.

A web application that delivers music and videos based on the user's emotional state.

Facial Emotion using FER13 dataset.

This project is a custom implementation of VGGNet trained to classify images of faces into 7 classes, representing different emotions.

A Federated Learning Platform For Facial Expression Recognition using the Flower framework and FER2013 dataset.