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Low Power Neuromorphic EMG Gesture Classification
In this work, we address the aforementioned gaps with following key contributions: (1) Low-power, high accuracy demonstration of EMG-signal based gesture recognition using neuromorphic Recurrent Spiking Neural Networks (RSNN).
Multi-Class Classification of Blood Cells -- End to End Computer Vision based diagnosis case study
Automated medical image processing and analysis offers a powerful tool for medical diagnosis.
Efficient Video Summarization Framework using EEG and Eye-tracking Signals
Therefore, the proposed paper considers human's role in summarization and introduces human visual attention-based summarization techniques.
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