FERPlus Dataset
FERPlus Dataset
Datasets
FERPlus Dataset
File
FERPlus
Use Case
FERPlus
Description
Explore the FERPlus dataset, featuring 78,299 meticulously annotated images categorized into eight emotions: Angry, Contempt, Disgust, Fear, Happy, Neutral, Sad, and Surprise.
Description:
The FERPlus builds upon the widely-used FER (Facial Expression Recognition) dataset, providing an enhanced and more granular set of labeled images for facial emotion recognition tasks. It includes over 30,000 grayscale images of faces, each categorized into eight distinct emotions: Angry, Contempt, Disgust, Fear, Happy, Neutral, Sad, and Surprise. One of the standout features of FERPlus is its crowdsourced labeling, where multiple annotators contributed to the classification of each image, resulting in more accurate and refined emotion labels compared to the original FER dataset.
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Dataset Details
- Image Size: 112 x 112 pixels
- Emotions Included: Angry, Contempt, Disgust, Fear, Happy, Neutral, Sad, Surprise
Structure
- Training Set: 66,379 images
- Validation Set: 8,341 images
- Test Set: 3,579 images
Enhanced Description and Usage
The FERPlus dataset is meticulously organized to support the development of highly accurate emotion recognition models. Each image is carefully annotated, ensuring reliable and precise labeling of emotions, which is crucial for training deep learning algorithms.
Potential Applications
- Psychological Research: Analyzing emotional responses in controlled experiments.
- Human-Computer Interaction: Enhancing user experience by incorporating emotion-aware systems.
- Marketing: Understanding consumer reactions to advertisements.
- Healthcare: Monitoring and interpreting patient emotions in therapeutic settings.
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