most citedMeta Batch-Instance Normalization for Generalizable Person Re-Identification

9 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20221 cited

Exploring Temporal Information Dynamics in Spiking Neural Networks

Youngeun Kim, Yuhang Li, Hyoungseob Park +3

Most existing Spiking Neural Network (SNN) works state that SNNs may utilize temporal information dynamics of spikes. However, an explicit analysis of temporal information dynamics…

cs.NE20227 cited

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks

Yuhang Li, Ruokai Yin, Hyoungseob Park +2

We study the Human Activity Recognition (HAR) task, which predicts user daily activity based on time series data from wearable sensors. Recently, researchers use end-to-end Artific…

cs.LG20225 cited

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization

Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park +2

Federated learning has been extensively studied and is the prevalent method for privacy-preserving distributed learning in edge devices. Correspondingly, continual learning is an e…

cs.NE2022

Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?

Youngeun Kim, Hyoungseob Park, Abhishek Moitra +3

Recent Spiking Neural Networks (SNNs) works focus on an image classification task, therefore various coding techniques have been proposed to convert an image into temporal binary s…

cs.CV20209 cited

Meta Batch-Instance Normalization for Generalizable Person Re-Identification

Seokeon Choi, Taekyung Kim, Minki Jeong +2

Although supervised person re-identification (Re-ID) methods have shown impressive performance, they suffer from a poor generalization capability on unseen domains. Therefore, gene…