Spiking neural networks for autonomous driving: A review

FS Martínez, J Casas-Roma, L Subirats… - … Applications of Artificial …, 2024 - Elsevier
The rapid progress of autonomous driving (AD) has triggered a surge in demand for safer
and more efficient autonomous vehicles, owing to the intricacy of modern urban …

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing

JE Pedersen, S Abreu, M Jobst, G Lenz, V Fra… - Nature …, 2024 - nature.com
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal
dynamics are getting wide attention and are being applied to many relevant problems using …

Brain-inspired computing: A systematic survey and future trends

G Li, L Deng, H Tang, G Pan, Y Tian… - Proceedings of the …, 2024 - ieeexplore.ieee.org
Brain-inspired computing (BIC) is an emerging research field that aims to build fundamental
theories, models, hardware architectures, and application systems toward more general …

From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?

MD Pham, A D'Angiulli, MM Dehnavi, R Chhabra - Brain Sciences, 2023 - mdpi.com
We examine the challenging “marriage” between computational efficiency and biological
plausibility—A crucial node in the domain of spiking neural networks at the intersection of …

Hippocampome. org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

DW Wheeler, JD Kopsick, N Sutton, C Tecuatl… - Elife, 2024 - elifesciences.org
Hippocampome. org is a mature open-access knowledge base of the rodent hippocampal
formation focusing on neuron types and their properties. Previously, Hippocampome. org v1 …

EdgeMap: an optimized map** toolchain for spiking neural network in edge computing

J Xue, L ** and benchmarking of spiking neural network hardware
S Matinizadeh, A Das - 2024 34th International Conference on …, 2024 - ieeexplore.ieee.org
Spiking neural networks (SNNs) are bioplausible machine learning models that use discrete
spikes to encode, compute, and transmit information. Combined with event-driven low …

[HTML][HTML] Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models

B Vallejo-Mancero, S Faci-Lázaro, M Zapata, J Soriano… - Neural Networks, 2024 - Elsevier
Biological neural networks are well known for their capacity to process information with
extremely low power consumption. Fields such as Artificial Intelligence, with high …