573 citations · 789 across the 12 of their papers we have counts for
14 papers
Event-Frame Fusion for Inter-Frame Segmentation via Event-Guided Motion
Dalia Hareb, Jean Martinet, Benoit Miramond +1
Autonomous navigation requires precise and efficient semantic segmentation, yet existing frame-based approaches remain limited by motion blur, glare, latency, and the low temporal…
Learning in Spiking Neural Networks with a Calcium-based Hebbian Rule for Spike-timing-dependent Plasticity
Willian Soares Girão, Nicoletta Risi, Elisabetta Chicca
Understanding how biological neural networks are shaped via local plasticity mechanisms can lead to energy-efficient and self-adaptive information processing systems, which promise…
Texture Recognition Using a Biologically Plausible Spiking Phase-Locked Loop Model for Spike Train Frequency Decomposition
Michele Mastella, Tesse Tiemens, Elisabetta Chicca
In this paper, we present a novel spiking neural network model designed to perform frequency decomposition of spike trains. Our model emulates neural microcircuits theorized in the…
A Comparison of Temporal Encoders for Neuromorphic Keyword Spotting with Few Neurons
Mattias Nilsson, Ton Juny Pina, Lyes Khacef +3
With the expansion of AI-powered virtual assistants, there is a need for low-power keyword spotting systems providing a "wake-up" mechanism for subsequent computationally expensive…
ETLP: Event-based Three-factor Local Plasticity for online learning with neuromorphic hardware
Fernando M. Quintana, Fernando Perez-Peña, Pedro L. Galindo +3
Neuromorphic perception with event-based sensors, asynchronous hardware and spiking neurons is showing promising results for real-time and energy-efficient inference in embedded sy…
Vector Symbolic Finite State Machines in Attractor Neural Networks
Madison Cotteret, Hugh Greatorex, Martin Ziegler +1
Hopfield attractor networks are robust distributed models of human memory, but lack a general mechanism for effecting state-dependent attractor transitions in response to input. We…