AndrzejMiskow/FER-with-Attention-and-Objective-Activation-Functions
This projected explored the effect of introducing channel and spatial attention mechanisms, namely SEN-Net, ECA-Net, and CBAM to existing CNN vision-based models such as VGGNet, ResNet, and ResNetV2 to perform the Facial Emotion Recognition task.
This project offers improved methods for automatically identifying human emotions from images of faces. It takes a facial image as input and outputs a classification of the emotion expressed (e.g., happy, sad, angry). Researchers and developers working on advanced computer vision applications will find this valuable.
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Use this if you are a researcher or developer building systems that need to accurately detect and classify facial emotions from image data.
Not ideal if you are looking for a ready-to-use application or a solution that does not require deep learning expertise.
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Jun 11, 2023
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