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  1. github.com › topics › facial-emotion-recognitionfacial-emotion-recognition · GitHub Topics · GitHub

    This Repo consist code for transfer learning for facial emotion detection via valence and arousal levels. We used pretrained weights from VGG-16 net and apply on that features deep neural network and lstm model in pytorch. We tested our model on Aff-wild net dataset.

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  3. github.com › topics › face-emotion-recognitionface-emotion-recognition · GitHub Topics · GitHub

    Face emotion recognition technology detects emotions and mood patterns invoked in human faces. This technology is used as a sentiment analysis tool to identify the six universal expressions, namely, happiness, sadness, anger, surprise, fear and disgust.

  4. github.com › ajitharunai › Facial-Emotionajitharunai/Facial-Emotion-Recognition-with-OpenCV-and-Deepface

    This project demonstrates the implementation of real-time facial emotion recognition using the deepface library and OpenCV. The objective is to capture live video from a webcam, identify faces within the video stream, and predict the corresponding emotions for each detected face. The emotions predicted are displayed in real-time on the video ...

  5. www.geeksforgeeks.org › emotion-detection-usingEmotion Detection Using Convolutional Neural Networks (CNNs)

    May 22, 2024 · Emotion detection, also known as facial emotion recognition, is a fascinating field within the realm of artificial intelligence and computer vision. It involves the identification and interpretation of human emotions from facial expressions.

  6. learnopencv.com › facial-emotion-recognitionFacial Emotion Recognition In Real-Time - LearnOpenCV

    • An Abstract Illustration of Multiple Emotions. Emotions have been linked to physical health outcomes. Understanding and managing emotions is crucial for mental wellbeing.
    • Real-Time Facial Emotion Recognition System in Action. Nevertheless, you might wonder, “What is the real use of facial emotion recognition systems?”
    • Various Classes of Emotions in FER+ v/s FER Datasets. This expansion of emotional categories in the FER+ dataset reflects a recognition of the complexity of human emotions and expressions.
    • Single Shot Multibox Detector Model Architecture. Custom VGG13 Model Architecture. The emotion recognition classification model employs a customized VGG13 architecture designed for 64×64 grayscale images.

  7. paperswithcode.com › task › facial-emotionFacial Emotion Recognition - Papers With Code

    To bridge this gap, we present the quantitative evaluation results of GPT-4V on 21 benchmark datasets covering 6 tasks: visual sentiment analysis, tweet sentiment analysis, micro-expression recognition, facial emotion recognition, dynamic facial emotion recognition, and multimodal emotion recognition. 81.

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  9. paperswithcode.com › facial-expression-recognitionFacial Expression Recognition (FER) - Papers With Code

    Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face such as eyebrows, eyes, mouth, and other features, and mapping them to a set of ...