Neuromorphic Solutions for Sensor Fusion and Continual Learning Systems: Applications in Drone Navigation and Radar Sensing

Ali Safa; Lars Keuninckx; Georges Gielen; Francky Catthoor

doi:10.1007/978-3-031-63565-6

Neuromorphic Solutions for Sensor Fusion and Continual Learning Systems: Applications in Drone Navigation and Radar Sensing

Ali Safa
, Lars Keuninckx
, Georges Gielen
, Francky Catthoor

Interuniversitair Micro-Elektronica Centrum
KU Leuven

Research output: Book/Report › Book › peer-review

2 Citations (Scopus)

Abstract

This book provides novel theoretical foundations and experimental demonstrations of Spiking Neural Networks (SNNs) in tasks such as radar gesture recognition for IoT devices and autonomous drone navigation using a fusion of retina-inspired event-based camera and radar sensing. The authors describe important new findings about the Spike-Timing-Dependent Plasticity (STDP) learning rule, which is widely believed to be one of the key learning mechanisms taking place in the brain. Readers will be enabled to create novel classes of edge AI and robotics applications, using highly energy- and area-efficient SNNs.

Original language	English
Publisher	Springer Nature
Number of pages	214
ISBN (Electronic)	9783031635656
ISBN (Print)	9783031635649
DOIs	https://doi.org/10.1007/978-3-031-63565-6
Publication status	Published - 1 Jan 2024
Externally published	Yes

Keywords

Neuromorphic Computing
Neuromorphic Sensor Fusion
Radar-SNN processing
Simultaneous Localization and Mapping
Spike-Timing-Dependent Plasticity
Spiking Neural Network

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10.1007/978-3-031-63565-6

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abstract = "This book provides novel theoretical foundations and experimental demonstrations of Spiking Neural Networks (SNNs) in tasks such as radar gesture recognition for IoT devices and autonomous drone navigation using a fusion of retina-inspired event-based camera and radar sensing. The authors describe important new findings about the Spike-Timing-Dependent Plasticity (STDP) learning rule, which is widely believed to be one of the key learning mechanisms taking place in the brain. Readers will be enabled to create novel classes of edge AI and robotics applications, using highly energy- and area-efficient SNNs.",

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AU - Keuninckx, Lars

AU - Gielen, Georges

AU - Catthoor, Francky

N1 - Publisher Copyright: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024/1/1

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N2 - This book provides novel theoretical foundations and experimental demonstrations of Spiking Neural Networks (SNNs) in tasks such as radar gesture recognition for IoT devices and autonomous drone navigation using a fusion of retina-inspired event-based camera and radar sensing. The authors describe important new findings about the Spike-Timing-Dependent Plasticity (STDP) learning rule, which is widely believed to be one of the key learning mechanisms taking place in the brain. Readers will be enabled to create novel classes of edge AI and robotics applications, using highly energy- and area-efficient SNNs.

AB - This book provides novel theoretical foundations and experimental demonstrations of Spiking Neural Networks (SNNs) in tasks such as radar gesture recognition for IoT devices and autonomous drone navigation using a fusion of retina-inspired event-based camera and radar sensing. The authors describe important new findings about the Spike-Timing-Dependent Plasticity (STDP) learning rule, which is widely believed to be one of the key learning mechanisms taking place in the brain. Readers will be enabled to create novel classes of edge AI and robotics applications, using highly energy- and area-efficient SNNs.

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KW - Simultaneous Localization and Mapping

KW - Spike-Timing-Dependent Plasticity

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ER -

Neuromorphic Solutions for Sensor Fusion and Continual Learning Systems: Applications in Drone Navigation and Radar Sensing

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