Boubker10/DeepLearningReconFacialSNN
This project represents an evolution of a pre-existing facial expression recognition (FER) system by leveraging Spiking Neural Networks (SNNs) and event cameras. We contributed to this field by optimizing the existing source code, training the improved model with the CKPLUS database, and conducting tests and evaluations to measure its performance
This project offers an advanced system for facial expression recognition using specialized event cameras, which are highly sensitive to changes in a visual scene. It takes raw event camera data, processes it through spiking neural networks, and outputs classifications of facial expressions like happiness, sadness, or surprise. Researchers and engineers working on emotion detection in real-time or low-power scenarios would find this particularly useful.
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Use this if you need highly responsive and energy-efficient facial expression recognition, especially when working with event camera data.
Not ideal if you primarily work with standard video footage or do not have access to event camera technology.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Jan 03, 2025
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