Efficient Epileptic Seizure Prediction Based on Deep Learning.

Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patients' life. In this paper, a novel patient-specific seizure prediction technique based on deep learning and applied to long-term scalp electroencephalogram (EEG) recordings is proposed.

Memory-efficient architecture for hysteresis thresholding and object feature extraction.

Hysteresis thresholding is a method that offers enhanced object detection. Due to its recursive nature, it is time consuming and requires a lot of memory resources. This makes it avoided in streaming processors with limited memory.