most citedData Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks

630 citations · 649 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY20193 cited

Transmission Power Control for Remote State Estimation in Industrial Wireless Sensor Networks

Samuele Zoppi, Touraj Soleymani, Markus Klügel +3

Novel low-power wireless technologies and IoT applications open the door to the Industrial Internet of Things (IIoT). In this new paradigm, Wireless Sensor Networks (WSNs) must ful…

eess.SY2019

Keep soft robots soft -- a data-driven based trade-off between feed-forward and feedback control

Thomas Beckers, Sandra Hirche

Tracking control for soft robots is challenging due to uncertainties in the system model and environment. Using high feedback gains to overcome this issue results in an increasing…

cs.LG201910 cited

Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves

Armin Lederer, Jonas Umlauft, Sandra Hirche

The posterior variance of Gaussian processes is a valuable measure of the learning error which is exploited in various applications such as safe reinforcement learning and control…

cs.RO20176 cited

Object Handover Prediction using Gaussian Processes clustered with Trajectory Classification

Muriel Lang, Satoshi Endo, Oliver Dunkley +1

A robotic system which approximates the user intention and appropriate complimentary motion is critical for successful human-robot interaction. %While the existing wearable sensors…

cs.CV2017630 cited

Data Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks

Terry Taewoong Um, Franz Michael Josef Pfister, Daniel Pichler +5

While convolutional neural networks (CNNs) have been successfully applied to many challenging classification applications, they typically require large datasets for training. When…