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View article: Epilepsy Seizure Detection and Prediction using an Approximate Spiking Convolutional Transformer
Epilepsy Seizure Detection and Prediction using an Approximate Spiking Convolutional Transformer Open
Epilepsy is a common disease of the nervous system. Timely prediction of seizures and intervention treatment can significantly reduce the accidental injury of patients and protect the life and health of patients. This paper presents a neur…
View article: FrameFire: Enabling Efficient Spiking Neural Network Inference for Video Segmentation
FrameFire: Enabling Efficient Spiking Neural Network Inference for Video Segmentation Open
Fast video recognition is essential for real-time scenarios, e.g., autonomous driving. However, applying existing Deep Neural Networks (DNNs) to individual high-resolution images is expensive due to large model sizes. Spiking Neural Networ…
View article: Enabling Energy-Efficient Inference for Self-Attention Mechanisms in Neural Networks
Enabling Energy-Efficient Inference for Self-Attention Mechanisms in Neural Networks Open
The study of specialized accelerators tailored for neural networks is becoming a promising topic in recent years. Such existing neural network accelerators are usually designed for convolutional neural networks (CNNs) or recurrent neural n…