1 citations · 1 across the 7 of their papers we have counts for
9 papers
Spiking Neural Network Actor-Critic Proximal Policy Optimization Control for Autonomous UAV Navigation Through Constrained Openings in Civil Infrastructure and Buildings
Francis Noah Walugembe, Maciej Wielgosz, Tomaž Goričan +1
Autonomous navigation of unmanned aerial vehicles in constrained three-dimensional environments has been a challenge in the robotics domain. The application of autonomous unmanned…
Unsupervised spiking feature learning for event-based pedestrian crossing detection: approaching supervised accuracy without labelled training data
Henok Teklu, Mustafa Sakhai, Matej Mertik +1
Event cameras are well suited to pedestrian crossing detection, and spiking neural networks (SNNs) can process their output natively, but current SNN detectors are trained with sup…
Pedestrian Crossing Intent Classification From Event-Based Vision Using Convolutional Spiking Neural Networks With Temporal Augmentation
Henok Teklu, Mustafa Sakhai, Maciej Wielgosz +1
Anticipating whether a pedestrian will cross the road is safety-critical for autonomous vehicles, requiring real-time inference under challenging conditions including motion blur,…
A Time-Multiplexed Spiking Neural Network Accelerator with Pipelined Readout for FPGA Inference
Reza Ansari, Maciej Wielgosz
Spiking Neural Networks (SNNs) provide a power-efficient neuromorphic alternative to traditional artificial neural networks by processing information through discrete temporal even…
InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making
Mustafa Sakhaia, Kaung Sithua, Min Khant Soe Okea +1
Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often struggle in high-dynamic- r…
Compression and Inference of Spiking Neural Networks on Resource-Constrained Hardware
Karol C. Jurzec, Tomasz Szydlo, Maciej Wielgosz
Spiking neural networks (SNNs) communicate via discrete spikes in time rather than continuous activations. Their event-driven nature offers advantages for temporal processing and e…
DVS-PedX: Synthetic-and-Real Event-Based Pedestrian Dataset
Mustafa Sakhai, Kaung Sithu, Min Khant Soe Oke +1
Event cameras like Dynamic Vision Sensors (DVS) report micro-timed brightness changes instead of full frames, offering low latency, high dynamic range, and motion robustness. DVS-P…
Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspective
Szymon Mazurek, Jakub Caputa, Jan K. Argasiński +1
Three-factor learning rules in Spiking Neural Networks (SNNs) have emerged as a crucial extension to traditional Hebbian learning and Spike-Timing-Dependent Plasticity (STDP), inco…
Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors
Mustafa Sakhai, Szymon Mazurek, Jakub Caputa +2
This study examines the effectiveness of Spiking Neural Networks (SNNs) paired with Dynamic Vision Sensors (DVS) to improve pedestrian detection in adverse weather, a significant c…