4 papers
Multi-Depth Temporal Fusion for Feedforward, Locally Trained Spiking Neural Networks
Aidin Attar, Eleonora Cicciarella, Michele Rossi
We propose a new spiking neural network (SNN) design to process static images and event streams using time-to-first-spike (TTFS) latencies. Our key research question is which archi…
Predictive Suppression Layers for Communication-Efficient Spiking Neural Networks
Aidin Attar, Michele Rossi
Feedforward Spiking Neural Networks (SNNs) typically propagate every generated spike indiscriminately, disregarding whether the information is redundant from an information-theoret…
Combining Convolution and Delay Learning in Recurrent Spiking Neural Networks
Lúcio Folly Sanches Zebendo, Eleonora Cicciarella, Michele Rossi
Spiking neural networks (SNNs) are rapidly gaining momentum as an alternative to conventional artificial neural networks in resource constrained edge systems. In this work, we cont…
Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices
Neda Shalavi, Aria Khoshsirat, Marco Stellini +2
Power efficiency is a crucial consideration for embedded systems design, particularly in the field of edge computing and IoT devices. This study aims to calibrate the power measure…