emotion-recognition-neural-networks and Emotion-detection
About emotion-recognition-neural-networks
isseu/emotion-recognition-neural-networks
Emotion recognition using DNN with tensorflow
This project helps researchers or students in the field of human-computer interaction or psychology to automatically categorize human emotions from facial images. It takes a collection of facial photographs as input and classifies them into one of seven emotional expressions (angry, disgusted, fearful, happy, sad, surprised, and neutral) as output. This would be used by someone studying emotional responses or building systems that react to user emotions.
About Emotion-detection
atulapra/Emotion-detection
Real-time Facial Emotion Detection using deep learning
This project helps you classify a person's real-time facial expressions into seven core emotions: angry, disgusted, fearful, happy, neutral, sad, and surprised. It takes live webcam video as input and outputs the detected emotion displayed on the screen. This is designed for researchers, developers, or anyone interested in exploring real-time human emotion recognition from video feeds.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work