Similarity between faces: One person resembles another person to a large degree. This can lead to many problems facing security surveillance systems. Facial recognition systems have difficulty distinguishing between the main person and other people who are highly similar in terms of features.

A curated list of facial expression recognition in both 7-emotion classification and affect estimation.

Facial Emotion Recognition using OpenCV and Deepface

Moodify is a Flask-based web application that seamlessly integrates facial emotion recognition (FER) with personalized music recommendations.

EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.

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

Analysis of Elicited and Acted Emotional Expressions in PEDFE

This project was a collaborative effort completed for a university course titled, "Making People Understand Facial Recognition Technologies: Building an AI Application as Didactic Tool".

Facial Emotion Recognition is a deep learning project focused on classifying facial expressions into different emotions. The project utilizes convolutional neural networks (CNNs) and is implemented using Keras.

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

Facial emotion recognition by using convolutional neural network (CNN)

This is a web application that takes different kind of inputs(real-time, image, video) from the user and display the emotion based on the facial expressions.

Emotion recognition with the FER-2013 Dataset

Model built using Python, Tensorflow, and Keras, that can accurately predict the emotion on a human face in an image.

A set of Google colab notebooks with my work on data analysis

Facial Recognition software using AWS EC2 , AWS-Rekognition and a Telegram bot

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

Screen mode eye and face tracking for VRChat

Multi-modal Human Emotion Recognition of speech clips (audio + video) contained in RAVDESS dataset using a two stream architecture