publié le: 2021
Approximate computing has emerged as an efficient design approach for applications with inherent error resilience. Low-power approximate adders (LPAAs...
High-throughput and low-latency Convolutional Neural Network (CNN) inference is increasingly important for many cloud- and edge-computing applications...
Computationally intensive neural network applications often need to run on resource-limited low-power devices. Numerous hardware accelerators have bee...
This article presents an energy-efficient and flexible multichannel Electroencephalogram (EEG) artifact identification network and its hardware using...
Convolutional/Deep Neural Networks (CNNs/DNNs) are rapidly growing workloads for the emerging AIbased systems. The gap between the processing speed an...
