GitHub topics: emotiondetection
carlthecoder123123/Realtime-emotion-detector
A deep learning-based system that detects facial expressions from webcam input and classifies them into seven emotions — Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise — using a CNN model and OpenCV for real-time face detection.
Language: Jupyter Notebook - Size: 63.5 KB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 3 - Forks: 0
kajendra10/EmotionDetector
Emotion Detector app to detect realtime facial expression using Kotlin.
Language: Kotlin - Size: 31.3 MB - Last synced at: 23 days ago - Pushed at: 24 days ago - Stars: 1 - Forks: 1
AnubhavChaturvedi-GitHub/Emotion-Recognition
Emotion Recognition is a cutting-edge deep learning project designed to detect and classify human emotions based on facial expressions. Using a Convolutional Neural Network (CNN), the model is trained on the FER2013 dataset and can accurately recognize seven distinct emotions
Language: Python - Size: 8.15 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 8 - Forks: 0
itubrainlab/eeg_preprocessing_pipeline
This pipeline was created as part of a 7.5 ECTS research project during the MSc in Software Design program at the IT University of Copenhagen. It is an EEG data preprocessing tool designed to support newcomers in preprocessing of EEG data. The pipeline outputs a cleaned EEG file in .fif format along with a detailed report.
Language: Python - Size: 415 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0
DataScienceVibes/Emotion_Detection-Using-Yolov5
Emotion detection typically categorizes emotions into basic or complex categories such as happiness, sadness, anger, fear, surprise, disgust, and sometimes more nuanced emotions like confusion, excitement, or trust. These categories can vary depending on the specific application and dataset.
Size: 21.4 MB - Last synced at: 5 months ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0
