emotion-recognition-neural-networks and Emotion-recognition
These tools are competitors, as both repositories provide real-time facial emotion recognition using deep neural networks, with one leveraging a general real-time approach and the other specifically mentioning TensorFlow and DNNs.
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-recognition
otaha178/Emotion-recognition
Real time emotion recognition
This tool helps analyze human facial expressions in real-time video streams, identifying emotions like happiness, anger, and more. It takes live camera footage of a person's face and outputs the likelihood of various emotions being displayed at that moment. This is useful for researchers studying non-verbal communication, UX designers observing user reactions, or marketers assessing engagement.
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