A survey of encoding techniques for signal processing in spiking neural networks
Biologically inspired spiking neural networks are increasingly popular in the field of artificial
intelligence due to their ability to solve complex problems while being power efficient. They …
intelligence due to their ability to solve complex problems while being power efficient. They …
Spiking neural networks for computational intelligence: an overview
Deep neural networks with rate-based neurons have exhibited tremendous progress in the
last decade. However, the same level of progress has not been observed in research on …
last decade. However, the same level of progress has not been observed in research on …
Unsupervised learning of a hierarchical spiking neural network for optical flow estimation: From events to global motion perception
F Paredes-Vallés, KYW Scheper… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The combination of spiking neural networks and event-based vision sensors holds the
potential of highly efficient and high-bandwidth optical flow estimation. This paper presents …
potential of highly efficient and high-bandwidth optical flow estimation. This paper presents …
Deep reinforcement learning with population-coded spiking neural network for continuous control
The energy-efficient control of mobile robots has become crucial as the complexity of their
real-world applications increasingly involves high-dimensional observation and action …
real-world applications increasingly involves high-dimensional observation and action …
Eventnet: Asynchronous recursive event processing
Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report
per-pixel intensity changes rather than outputting an actual intensity image at regular …
per-pixel intensity changes rather than outputting an actual intensity image at regular …
Spiking neural network on neuromorphic hardware for energy-efficient unidimensional slam
G Tang, A Shah, KP Michmizos - 2019 IEEE/RSJ International …, 2019 - ieeexplore.ieee.org
Energy-efficient simultaneous localization and mapping (SLAM) is crucial for mobile robots
exploring unknown environments. The mammalian brain solves SLAM via a network of …
exploring unknown environments. The mammalian brain solves SLAM via a network of …
Reinforcement co-learning of deep and spiking neural networks for energy-efficient mapless navigation with neuromorphic hardware
Energy-efficient mapless navigation is crucial for mobile robots as they explore unknown
environments with limited on-board resources. Although the recent deep rein-forcement …
environments with limited on-board resources. Although the recent deep rein-forcement …
[HTML][HTML] Human-inspired autonomous driving: A survey
Autonomous vehicles promise to revolutionize society and improve the daily life of many,
making them a coveted aim for a vast research community. To enable complex reasoning in …
making them a coveted aim for a vast research community. To enable complex reasoning in …
Bio-plausible digital implementation of a reward modulated STDP synapse
Abstract Reward-modulated Spike-Timing-Dependent Plasticity (R-STDP) is a learning
method for Spiking Neural Network (SNN) that makes use of an external learning signal to …
method for Spiking Neural Network (SNN) that makes use of an external learning signal to …
Fully neuromorphic vision and control for autonomous drone flight
Biological sensing and processing is asynchronous and sparse, leading to low-latency and
energy-efficient perception and action. In robotics, neuromorphic hardware for event-based …
energy-efficient perception and action. In robotics, neuromorphic hardware for event-based …