Spiking neural networks for autonomous driving: A review
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 …
and more efficient autonomous vehicles, owing to the intricacy of modern urban …
Spiking neural networks for frame-based and event-based single object localization
Spiking neural networks (SNNs) have shown much promise as an energy-efficient
alternative to artificial neural networks (ANNs). Such methods trained by surrogate gradient …
alternative to artificial neural networks (ANNs). Such methods trained by surrogate gradient …
A single chip spad based vision sensing system with integrated memristive spiking neuromorphic processing
This paper presents a new scalable single photon avalanche diode (SPAD) based vision
sensor with integrated spiking neuromorphic system on a single chip. The proposed vision …
sensor with integrated spiking neuromorphic system on a single chip. The proposed vision …
Review of Neuromorphic Processing for Vision Sensors
Traditionally, vision sensors generate large amounts of redundant spatiotemporal data that
are transferred to an off-chip processor for processing, limiting frame rates. Additionally …
are transferred to an off-chip processor for processing, limiting frame rates. Additionally …
Real-time classification of LIDAR data using discrete-time Recurrent Spiking Neural Networks
With the advancement of Edge AI and autonomous systems, AI applications are increasingly
subject to energy, latency and environmental constraints. Biological neural systems naturally …
subject to energy, latency and environmental constraints. Biological neural systems naturally …
Exploring deep spiking neural networks for automated driving applications
Neural networks have become the standard model for various computer vision tasks in
automated driving including semantic segmentation, moving object detection, depth …
automated driving including semantic segmentation, moving object detection, depth …
[PDF][PDF] SpikiLi: A Spiking Simulation of Lidar based Object Detection
Spiking Neural Networks are a recent and new neural network design approach that
promises tremendous improvements in power efficiency, computation efficiency, and …
promises tremendous improvements in power efficiency, computation efficiency, and …
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving
S Mohapatra, T Mesquida, M Hodaei… - … Conference on Event …, 2022 - ieeexplore.ieee.org
Spiking Neural Networks are a recent and new neural network design approach that
promises tremendous improvements in power efficiency, computation efficiency, and …
promises tremendous improvements in power efficiency, computation efficiency, and …
[PDF][PDF] Potentials of Neuromorphic Computing for Automated Driving and Future Transportation Systems
L Bayerlein, JV Schulte, S Peters - uni-das.de
Neuromorphic computing, inspired by the structure and functionality of the human brain,
offers a transformative potential for advancing automated driving systems. This review …
offers a transformative potential for advancing automated driving systems. This review …
Classifying information using spiking neural network
C Grassmann - US Patent App. 16/725,598, 2020 - Google Patents
A semiconductor device is provided. The semiconductor device may comprise a circuit
configured to generate information. The semiconductor device may comprise a monitoring …
configured to generate information. The semiconductor device may comprise a monitoring …