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Found 14 papers, 3 papers with code
Continual Learning for Autonomous Robots: A Prototype-based Approach
Humans and animals learn throughout their lives from limited amounts of sensed data, both with and without supervision.
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings.
Neuromorphic Visual Odometry with Resonator Networks
The VO network we propose generates and stores a working memory of the presented visual environment.
Neuromorphic Visual Scene Understanding with Resonator Networks
Understanding a visual scene by inferring identities and poses of its individual objects is still and open problem.
What does it mean to represent? Mental representations as falsifiable memory patterns
Representation is a key notion in neuroscience and artificial intelligence (AI).
Event-driven Vision and Control for UAVs on a Neuromorphic Chip
Here, we explore how an event-based vision algorithm can be implemented as a spiking neuronal network on a neuromorphic chip and used in a drone controller.
Visual Pattern Recognition with on On-chip Learning: towards a Fully Neuromorphic Approach
We present a spiking neural network (SNN) for visual pattern recognition with on-chip learning on neuromorphichardware.
Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors
The Lobula Giant Movement Detector (LGMD) is an identified neuron of the locust that detects looming objects and triggers the insect's escape responses.
Event-based attention and tracking on neuromorphic hardware
We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS.
Closing the Accuracy Gap in an Event-Based Visual Recognition Task
Mobile and embedded applications require neural networks-based pattern recognition systems to perform well under a tight computational budget.
The importance of space and time in neuromorphic cognitive agents
This efficiency and adaptivity gap is partially explained by the computing substrate of biological neural processing systems that is fundamentally different from the way today's computers are built.
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor
In this paper, we present a spiking neural network architecture that uses sensory feedback to control rotational velocity of a robotic vehicle.
Differential Evolution and Bayesian Optimisation for Hyper-Parameter Selection in Mixed-Signal Neuromorphic Circuits Applied to UAV Obstacle Avoidance
We also investigate the use of Self-Adaptive Differential Evolution (SADE) which has been shown to ameliorate the difficulties of finding appropriate input parameters for DE.
Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
We introduce a dynamic neural algorithm called Dynamic Neural (DN) SARSA(\lambda) for learning a behavioral sequence from delayed reward.
