3 citations · 3 across the 6 of their papers we have counts for
7 papers
Logic Gate Networks and Lookup Table Networks as Lightweight Hardware Classifiers for Inter-patient ECG Arrhythmia Classification
Wout Mommen, Lars Keuninckx, Siddharth Patil +3
Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) offer a promising approach for very low power inference due to their use of simple binary logic ope…
Inter-patient ECG Arrhythmia Classification with LGNs and LUTNs
Wout Mommen, Lars Keuninckx, Paul Detterer +2
Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) are demonstrated to be suitable for the automatic classification of electrocardiograms (ECGs) using…
Efficient Synaptic Delay Implementation in Digital Event-Driven AI Accelerators
Roy Meijer, Paul Detterer, Amirreza Yousefzadeh +8
Synaptic delay parameterization of neural network models have remained largely unexplored but recent literature has been showing promising results, suggesting the delay parameteriz…
Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning
Lucas Huijbregts, Liu Hsiao-Hsuan, Paul Detterer +3
Current Artificial Intelligence (AI) computation systems face challenges, primarily from the memory-wall issue, limiting overall system-level performance, especially for Edge devic…
TRIP: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-based Vision
Cina Arjmand, Yingfu Xu, Kevin Shidqi +6
Neuromorphic processors are well-suited for efficiently handling sparse events from event-based cameras. However, they face significant challenges in the growth of computing demand…
EON-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction
Alexandra Dobrita, Amirreza Yousefzadeh, Simon Thorpe +8
For Edge AI applications, deploying online learning and adaptation on resource-constrained embedded devices can deal with fast sensor-generated streams of data in changing environm…
Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design
Guangzhi Tang, Ali Safa, Kevin Shidqi +6
Sparse and event-driven spiking neural network (SNN) algorithms are the ideal candidate solution for energy-efficient edge computing. Yet, with the growing complexity of SNN algori…