3 citations · 5 across the 8 of their papers we have counts for
9 papers
A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition
Mengxi Liu, Sungho Suh, Juan Felipe Vargas +3
In the human activity recognition research area, prior studies predominantly concentrate on leveraging advanced algorithms on public datasets to enhance recognition performance, li…
Learning from the Best: Contrastive Representations Learning Across Sensor Locations for Wearable Activity Recognition
Vitor Fortes Rey, Sungho Suh, Paul Lukowicz
We address the well-known wearable activity recognition problem of having to work with sensors that are non-optimal in terms of information they provide but have to be used due to…
Estimation of 3D Body Shape and Clothing Measurements from Frontal- and Side-view Images
Kundan Sai Prabhu Thota, Sungho Suh, Bo Zhou +1
The estimation of 3D human body shape and clothing measurements is crucial for virtual try-on and size recommendation problems in the fashion industry but has always been a challen…
Adversarial Deep Feature Extraction Network for User Independent Human Activity Recognition
Sungho Suh, Vitor Fortes Rey, Paul Lukowicz
User dependence remains one of the most difficult general problems in Human Activity Recognition (HAR), in particular when using wearable sensors. This is due to the huge variabili…
Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks
Sungho Suh, Paul Lukowicz, Yong Oh Lee
Bearing is a key component in industrial machinery and its failure may lead to unwanted downtime and economic loss. Hence, it is necessary to predict the remaining useful life (RUL…
Supervised Segmentation with Domain Adaptation for Small Sampled Orbital CT Images
Sungho Suh, Sojeong Cheon, Wonseo Choi +6
Deep neural networks (DNNs) have been widely used for medical image analysis. However, the lack of access a to large-scale annotated dataset poses a great challenge, especially in…