1 citations · 2 across the 5 of their papers we have counts for
5 papers
Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning
Ali Safa, Tim Verbelen, Ilja Ocket +4
This work proposes a first-of-its-kind SLAM architecture fusing an event-based camera and a Frequency Modulated Continuous Wave (FMCW) radar for drone navigation. Each sensor is pr…
Continuously Learning to Detect People on the Fly: A Bio-inspired Visual System for Drones
Ali Safa, Ilja Ocket, André Bourdoux +3
This paper demonstrates for the first time that a biologically-plausible spiking neural network (SNN) equipped with Spike-Timing-Dependent Plasticity (STDP) can continuously learn…
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
Ali Safa, Tim Verbelen, Ilja Ocket +3
Drones are currently being explored for safety-critical applications where human agents are expected to evolve in their vicinity. In such applications, robust people avoidance must…
A 2-J, 12-class, 91% Accuracy Spiking Neural Network Approach For Radar Gesture Recognition
Ali Safa, André Bourdoux, Ilja Ocket +2
Radar processing via spiking neural networks (SNNs) has recently emerged as a solution in the field of ultra-low-power wireless human-computer interaction. Compared to traditional…
A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance
Ali Safa, Tim Verbelen, Lars Keuninckx +5
As radar sensors are being miniaturized, there is a growing interest for using them in indoor sensing applications such as indoor drone obstacle avoidance. In those novel scenarios…