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Found 6 papers, 1 papers with code
Active Inference in Hebbian Learning Networks
This work studies how brain-inspired neural ensembles equipped with local Hebbian plasticity can perform active inference (AIF) in order to control dynamical agents.
Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning
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.
Continuously Learning to Detect People on the Fly: A Bio-inspired Visual System for Drones
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 to detect walking people on the fly using retina-inspired, event-based cameras.
A New Look at Spike-Timing-Dependent Plasticity Networks for Spatio-Temporal Feature Learning
We present new theoretical foundations for unsupervised Spike-Timing-Dependent Plasticity (STDP) learning in spiking neural networks (SNNs).
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
Currently however, people detection systems used on drones are solely based on standard cameras besides an emerging number of works discussing the fusion of imaging and event-based cameras.
A 2-$μ$J, 12-class, 91% Accuracy Spiking Neural Network Approach For Radar Gesture Recognition
Radar processing via spiking neural networks (SNNs) has recently emerged as a solution in the field of ultra-low-power wireless human-computer interaction.
