Using Keras (Tensorflow), CNN and OpenCV, this model accurately identifies emotions from facial expressions in real-time video streams.

Python code to detect human facial emotion with convolution neural network(CNN) a deep learning technique using haar cascade classifier.

"Face Expression Recognition Dataset" is a dataset of facial images labeled with the corresponding emotion. This repository contains code for data exploration, analysis, and modeling using this dataset.

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

This project is a web-based application that uses deep learning and computer vision to detect facial emotions in real time from a webcam feed. The app is powered by a pre-trained Convolutional Neural Network (CNN) and features a modern, user-friendly interface built with Streamlit.

A real-time facial emotion recognition system using DenseNet121 CNN, detecting emotions like happy, sad, angry, and surprise from webcam or image input. The system maps emotions to emojis, enhancing interaction. Built with TensorFlow, Keras, and OpenCV, this project showcases deep learning in human-computer interaction.