Federated Learning (FL) is a privacy-preserving distributed machine lear...
Spiking Neural Networks (SNNs) are recognized as the candidate for the
n...
Most existing Spiking Neural Network (SNN) works state that SNNs may uti...
We study the Human Activity Recognition (HAR) task, which predicts user ...
Spiking Neural Networks (SNNs) have recently emerged as a new generation...
Federated learning has been extensively studied and is the prevalent met...
Developing neuromorphic intelligence on event-based datasets with spikin...
Recent Spiking Neural Networks (SNNs) works focus on an image classifica...
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
Federated learning is a paradigm that enables local devices to jointly t...
Although supervised person re-identification (Re-ID) methods have shown
...
Domain adaptation assumes that samples from source and target domains ar...