[HTML][HTML] Efficient SNN multi-cores MAC array acceleration on SpiNNaker 2
The potential low-energy feature of the spiking neural network (SNN) engages the attention
of the AI community. Only CPU-involved SNN processing inevitably results in an inherently …
of the AI community. Only CPU-involved SNN processing inevitably results in an inherently …
Federated Learning for Radar Gesture Recognition Based on Spike Timing Dependent Plasticity
Radar-based gesture recognition combined machine learning methods can achieve
excellent performance and has been utilized in a wide variety of applications. However …
excellent performance and has been utilized in a wide variety of applications. However …
RT-SCNNs: real-time spiking convolutional neural networks for a novel hand gesture recognition using time-domain mm-wave radar data
This study introduces a novel approach to radar-based hand gesture recognition (HGR),
addressing the challenges of energy efficiency and reliability by employing real-time gesture …
addressing the challenges of energy efficiency and reliability by employing real-time gesture …
Hybrid Spiking and Artificial Neural Networks for Radar-Based Gesture Recognition
P Gerhards, M Weih, J Huang… - … on Frontiers of …, 2023 - ieeexplore.ieee.org
Artificial neural networks showed astonishing results in the last decades. However, they tend
to consume large amounts of energy which is problematic on edge devices such as …
to consume large amounts of energy which is problematic on edge devices such as …
Augmenting Radar Data via Sampling from Learned Latent Space
Data augmentation is a widely used technique to regularize deep learning models. It is
especially famous in computer vision due to its simplicity to apply. Literature suggests …
especially famous in computer vision due to its simplicity to apply. Literature suggests …