Sander Stuijk
YOU?
Author Swipe
View article: A Flexible Multi-Core Hardware Architecture for Stereo-Based Depth Estimation CNNs
A Flexible Multi-Core Hardware Architecture for Stereo-Based Depth Estimation CNNs Open
Stereo-based depth estimation is becoming more and more important in many applications like self-driving vehicles, earth observation, cartography, robotics and so on. Modern approaches to depth estimation employ artificial intelligence tec…
View article: Thermal Cameras for Overnight Measuring of Respiration in a Clinical Setting
Thermal Cameras for Overnight Measuring of Respiration in a Clinical Setting Open
Thermal imaging is a non-contact method for monitoring respiration activity during sleep. In this study, we evaluated its clinical application during overnight recordings in a sleep clinic. Five thermal cameras were used to detect breaths,…
View article: Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks
Traces Propagation: Memory-Efficient and Scalable Forward-Only Learning in Spiking Neural Networks Open
Spiking Neural Networks (SNNs) provide an efficient framework for processing dynamic spatio-temporal signals and for investigating the learning principles underlying biological neural systems. A key challenge in training SNNs is to solve b…
View article: Camera-Based Continuous Heart and Respiration Rate Monitoring in the ICU
Camera-Based Continuous Heart and Respiration Rate Monitoring in the ICU Open
We provide new insights into the performance of camera-based heart and respiration rate extraction and evaluate its usability for replacing spot checks conducted in the general ward. A study was performed comprising of 36 ICU patients reco…
View article: STEMS: Spatial-Temporal Mapping Tool For Spiking Neural Networks
STEMS: Spatial-Temporal Mapping Tool For Spiking Neural Networks Open
Spiking Neural Networks (SNNs) are promising bio-inspired third-generation neural networks. Recent research has trained deep SNN models with accuracy on par with Artificial Neural Networks (ANNs). Although the event-driven and sparse natur…
View article: Accuracy of remote, video-based supraventricular tachycardia detection in patients undergoing elective electrical cardioversion: a prospective cohort
Accuracy of remote, video-based supraventricular tachycardia detection in patients undergoing elective electrical cardioversion: a prospective cohort Open
Unobtrusive pulse rate monitoring by continuous video recording, based on remote photoplethysmography (rPPG), might enable early detection of perioperative arrhythmias in general ward patients. However, the accuracy of an rPPG-based machin…
View article: Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs
Hardware-In-The-Loop Training of a 4f Optical Correlator with Logarithmic Complexity Reduction for CNNs Open
This work evaluates a forward-only learning algorithm on the MNIST dataset with hardware-in-the-loop training of a 4f optical correlator, achieving 87.6% accuracy with O(n2) complexity, compared to backpropagation, which achieves 88.8% acc…
View article: Thermal Cameras for Continuous and Contactless Respiration Monitoring
Thermal Cameras for Continuous and Contactless Respiration Monitoring Open
Continuous respiration monitoring is an important tool in assessing the patient’s health and diagnosing pulmonary, cardiovascular, and sleep-related breathing disorders. Various techniques and devices, both contact and contactless, can be …
View article: Speckle Vibrometry for Contactless Instantaneous Heart Rate and Respiration Rate Monitoring on Mechanically Ventilated Patients
Speckle Vibrometry for Contactless Instantaneous Heart Rate and Respiration Rate Monitoring on Mechanically Ventilated Patients Open
Objective: Contactless monitoring of instantaneous heart rate and respiration rate has a significant clinical relevance. This work aims to use Speckle Vibrometry (i.e., based on the secondary laser speckle effect) to contactlessly measure …
View article: Probabilistic inference in the era of tensor networks and differential programming
Probabilistic inference in the era of tensor networks and differential programming Open
Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in…
View article: On the Importance of the Execution Schedule for Bayesian Inference
On the Importance of the Execution Schedule for Bayesian Inference Open
Bayesian inference is a probabilistic approach to the problem of drawing conclusions from observed data. Its main challenge is computational, which the Bayesian community tends to address through approximation techniques. However, these te…
View article: DNN-Based Visual Perception for High-Precision Motion Control
DNN-Based Visual Perception for High-Precision Motion Control Open
The high-speed, high-precision positioning of objects is a critical component in various industrial manufacturing processes. The semiconductor die packaging, for instance, requires the precise pickup and placement of semiconductor dies on …
View article: Probabilistic Inference in the Era of Tensor Networks and Differential Programming
Probabilistic Inference in the Era of Tensor Networks and Differential Programming Open
Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in…
View article: How Much Can We Gain From Tensor Kernel Fusion on GPUs?
How Much Can We Gain From Tensor Kernel Fusion on GPUs? Open
Kernel fusion is a crucial optimization technique for GPU applications, particularly deep neural networks, where it involves combining multiple consecutive kernels into a single larger kernel. This approach aims to enhance performance by r…
View article: Vision-Based Multi-Size Object Positioning
Vision-Based Multi-Size Object Positioning Open
<p>Accurate object positioning is critical in many industrial manufacturing applications. The execution time and precision of the object positioning task have a significant impact on the overall performance and throughput, especially…
View article: Thermal Imaging for Respiration Monitoring in Sleeping Positions: A Single Camera is Enough
Thermal Imaging for Respiration Monitoring in Sleeping Positions: A Single Camera is Enough Open
Polysomnography, the current gold standard for sleep monitoring, uses multiple obtrusive contact sensors for the assessment of respiration and flow. This could partially be overcome by using thermal cameras. For accurate estimation of brea…
View article: Scaling Probabilistic Inference Through Message Contraction Optimization
Scaling Probabilistic Inference Through Message Contraction Optimization Open
Within the realm of probabilistic graphical models, message-passing algorithms offer a powerful framework for efficient inference. When dealing with discrete variables, these algorithms essentially amount to the addition and multiplication…
View article: Speckle Vibrometry for Instantaneous Heart Rate Monitoring
Speckle Vibrometry for Instantaneous Heart Rate Monitoring Open
Instantaneous heart rate (IHR) has been investigated for sleep applications, such as sleep apnea detection and sleep staging. To ensure the comfort of the patient during sleep, it is desirable for IHR to be measured in a contact-free fashi…
View article: Dependability of Future Edge-AI Processors: Pandora’s Box
Dependability of Future Edge-AI Processors: Pandora’s Box Open
This paper addresses one of the directions of the HORIZON EU CONVOLVE project being dependability of smart edge processors based on computation-in-memory and emerging memristor devices such as RRAM. It discusses how how this alternative co…
View article: Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion Open
Dataset Introduction The advent of neural networks capable of learning salient features from variance in the radar data has expanded the breadth of radar applications, often as an alternative sensor or a complementary modality to camera vi…
View article: Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion Open
Dataset Introduction The advent of neural networks capable of learning salient features from variance in the radar data has expanded the breadth of radar applications, often as an alternative sensor or a complementary modality to camera vi…
View article: Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion Open
Dataset Introduction The advent of neural networks capable of learning salient features from variance in the radar data has expanded the breadth of radar applications, often as an alternative sensor or a complementary modality to camera vi…
View article: Respiration extraction and atrial fibrillation detection from clinical data based on single RGB camera
Respiration extraction and atrial fibrillation detection from clinical data based on single RGB camera Open
In this work, we investigated the feasibility of extracting continuous respiratory parameters from a single RGB camera stationed in a short-stay ward. Based on the extracted respiration parameters, we further investigated the feasibility o…
View article: PetaOps/W edge-AI $\mu$ Processors: Myth or reality?
PetaOps/W edge-AI $\mu$ Processors: Myth or reality? Open
With the rise of deep learning (DL), our world braces for artificial intelligence (AI) in every edge device, creating an urgent need for edge-AI SoCs. This SoC hardware needs to support high throughput, reliable and secure AI processing at…
View article: ReMeCo
ReMeCo Open
Memristor-based in-memory neuromorphic computing systems promise a highly efficient implementation of vector-matrix multiplications, commonly used in artificial neural networks (ANNs). However, the immature fabrication process of memristor…
View article: CONVOLVE: Smart and seamless design of smart edge processors
CONVOLVE: Smart and seamless design of smart edge processors Open
With the rise of Deep Learning (DL), our world braces for AI in every edge device, creating an urgent need for edge-AI SoCs. This SoC hardware needs to support high throughput, reliable and secure AI processing at Ultra Low Power (ULP), wi…
View article: Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numeric Behaviors
Dissecting Tensor Cores via Microbenchmarks: Latency, Throughput and Numeric Behaviors Open
Tensor Cores have been an important unit to accelerate Fused Matrix Multiplication Accumulation (MMA) in all NVIDIA GPUs since Volta Architecture. To program Tensor Cores, users have to use either legacy wmma APIs or current mma APIs. Lega…
View article: LEAPER: Fast and Accurate FPGA-based System Performance Prediction via Transfer Learning
LEAPER: Fast and Accurate FPGA-based System Performance Prediction via Transfer Learning Open
Machine learning has recently gained traction as a way to overcome the slow accelerator generation and implementation process on an FPGA. It can be used to build performance and resource usage models that enable fast early-stage design spa…
View article: DNAsim: Evaluation Framework for Digital Neuromorphic Architectures
DNAsim: Evaluation Framework for Digital Neuromorphic Architectures Open
Neuromorphic architectures implement low-power machine learning applications using spike-based biological neuron models trained with bio-inspired or machine learning algorithms. Prior work on simulating Spiking Neural Networks (SNNs) focus…