5 papers
Exploring the Trade-Off Between Structured Pruning and Fault Tolerance in Deep Neural Networks for Space Applications
Toon Vinck, Naïn Jonckers, Jaro De Roose +2
Deep Neural Networks (DNNs) inherently exhibit a degree of robustness to bit-level faults due to their distributed representation of information. As a model increases in width, thi…
A comparison between ceiling-mounted FMCW, IR-UWB and Wi-Fi radar for in-bedroom human activity monitoring and sleep interruption detection
Anton Lambrecht, Reda El Hail, Xianjun Jiao +5
Despite their growing importance for contact-free radio frequency (RF) based healthcare monitoring, different radio technologies such as frequency-modulated continuous wave (FMCW)…
Analysis of Single Event Induced Bit Faults in a Deep Neural Network Accelerator Pipeline
Naïn Jonckers, Toon Vinck, Peter Karsmakers +1
In recent years, the increased interest and the growth in application domains of Artificial Intelligence (AI), and more specifically Deep Neural Networks (DNNs), has led to an exte…
Mitigating multiple single-event upsets during deep neural network inference using fault-aware training
Toon Vinck, Naïn Jonckers, Gert Dekkers +2
Deep neural networks (DNNs) are increasingly used in safety-critical applications. Reliable fault analysis and mitigation are essential to ensure their functionality in harsh envir…
Single-Event Upset Analysis of a Systolic Array based Deep Neural Network Accelerator
Naïn Jonckers, Toon Vinck, Gert Dekkers +2
Deep Neural Network (DNN) accelerators are extensively used to improve the computational efficiency of DNNs, but are prone to faults through Single-Event Upsets (SEUs). In this wor…