Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

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This paper focuses on the operational characteristics of a medium voltage resonant DC transformer based on a split capacitor IGCT 3L-NPC leg. The study delves into both the dynamic and static balancing aspects of the 3L-NPC when operating in a two-level, 5 ...

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Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical resul ...

The medium-voltage (MV) dual active bridge (DAB) converter with series-connected SiC (S-SiC) MOSFETs is a promising solution for high-power-density isolated dc/dc converter. To improve the voltage sharing and reliability of S-SiC, relatively large snubber ...

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Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

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The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

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Ultrafast ultrasound imaging achieves high frame rates but results in lower image quality compared to focused acquisitions. Convolutional neural networks (CNNs) have emerged as effective tools for reducing diffraction artifacts and enhancing the quality of ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

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We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

Machine learning has transformed many fields and has recently found applications in chemistry and materials science. The small datasets commonly found in chemistry sparked the development of sophisticated machine learning approaches that incorporate chemic ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

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Static and Dynamic Voltage Balancing for an IGCT-Based Resonant DC Transformer

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

EdgeAI-Aware Design of In-Memory Computing Architectures

High-performance deep spiking neural networks with 0.3 spikes per neuron

Phase Shift Angle Segmentation Modulation for Soft-Switching Medium-Voltage DAB Converter With Series-Connected SiC MOSFETs

Accelerating Dynamic Aperture Evaluation Using Deep Neural Networks

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Understanding generalization and robustness in modern deep learning

Enhancement of Ultrafast Ultrasound Images: A Performance Comparison Between CNN Trained with RF or IQ Images

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Using Physical Dynamics: Accurate and Real-Time Object Detection for High-Resolution Video Streaming on Internet of Things Devices

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Leveraging large language models for predictive chemistry

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms