Search Results for author:
Found 7 papers, 3 papers with code
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.
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.
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware
To our knowledge, this is the first work to show a Spiking Neural Network (SNN) implementation of the backpropagation algorithm that is fully on-chip, without a computer in the loop.
Ranked #31 on
Image Classification
on MNIST
(Accuracy metric)
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.
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.
