Burkhard Hoppenstedt
Burkhard Hoppenstedt
Institute of Databases and Information Systems, Ulm University
Verified email at uni-ulm.de - Homepage
Title
Cited by
Cited by
Year
Techniques and emerging trends for state of the art equipment maintenance systems—a bibliometric analysis
B Hoppenstedt, R Pryss, B Stelzer, F Meyer-Brötz, K Kammerer, A Treß, ...
Applied Sciences 8 (6), 916, 2018
182018
Anomaly detections for manufacturing systems based on sensor data—insights into two challenging real-world production settings
K Kammerer, B Hoppenstedt, R Pryss, S Stökler, J Allgaier, M Reichert
Sensors 19 (24), 5370, 2019
172019
Applicability of immersive analytics in mixed reality: Usability study
B Hoppenstedt, T Probst, M Reichert, W Schlee, K Kammerer, ...
IEEE Access 7, 71921-71932, 2019
112019
Machine learning findings on geospatial data of users from the trackyourstress mhealth crowdsensing platform
R Pryss, D John, M Reichert, B Hoppenstedt, L Schmid, W Schlee, ...
2019 IEEE 20th International Conference on Information Reuse and Integration …, 2019
102019
Applying Machine Learning to Daily-Life Data From the TrackYourTinnitus Mobile Health Crowdsensing Platform to Predict the Mobile Operating System Used With High Accuracy …
R Pryss, W Schlee, B Hoppenstedt, M Reichert, M Spiliopoulou, ...
Journal of Medical Internet Research 22 (6), e15547, 2020
82020
Ecological momentary assessment based differences between Android and iOS Users of the trackyourhearing mhealth crowdsensing platform
R Pryss, W Schlee, M Reichert, I Kurthen, N Giroud, L Jagoda, ...
2019 41st Annual International Conference of the IEEE Engineering in …, 2019
72019
Convolutional neural networks for image recognition in mixed reality using voice command labeling
B Hoppenstedt, K Kammerer, M Reichert, M Spiliopoulou, R Pryss
International Conference on Augmented Reality, Virtual Reality and Computer …, 2019
72019
Debugging Quadrocopter Trajectories in Mixed Reality
B Hoppenstedt, T Witte, J Ruof, K Kammerer, M Tichy, M Reichert, R Pryss
International Conference on Augmented Reality, Virtual Reality and Computer …, 2019
52019
Process-driven and flow-based processing of industrial sensor data
K Kammerer, R Pryss, B Hoppenstedt, K Sommer, M Reichert
Sensors 20 (18), 5245, 2020
42020
Analysis of fuel cells utilizing mixed reality and IoT achievements
B Hoppenstedt, M Schmid, K Kammerer, J Scholta, M Reichert, R Pryss
International Conference on Augmented Reality, Virtual Reality and Computer …, 2019
32019
Dimensionality reduction and subspace clustering in mixed reality for condition monitoring of high-dimensional production data
B Hoppenstedt, M Reichert, K Kammerer, T Probst, W Schlee, ...
Sensors 19 (18), 3903, 2019
32019
Towards a Hierarchical Approach for Outlier Detection in Industrial Production Settings
B Hoppenstedt, M Reichert, K Kammerer, M Spiliopoulou, R Pryss
CEUR-WS. org, 2019
32019
HOLOVIEW: Exploring patient data in mixed reality
B Hoppenstedt, C Schneider, R Pryss, W Schlee, T Probst, P Neff, ...
32018
Evaluating usability aspects of a mixed reality solution for immersive analytics in industry 4.0 scenarios
B Hoppenstedt, T Probst, M Reichert, W Schlee, K Kammerer, ...
JoVE (Journal of Visualized Experiments), e61349, 2020
12020
CONSENSORS: A Neural Network Framework for Sensor Data Analysis
B Hoppenstedt, R Pryss, K Kammerer, M Reichert
OTM Confederated International Conferences" On the Move to Meaningful …, 2018
12018
Exploring dimensionality reduction effects in mixed reality for analyzing tinnitus patient data
B Hoppenstedt, M Reichert, C Schneider, K Kammerer, W Schlee, ...
12018
Datengetriebene Module für Predictive Maintenance
B Hoppenstedt, R Pryss, A Treß, B Biechele, M Reichert
ProductivITy 22, 21-23, 2017
12017
Detecting Production Phases Based on Sensor Values using 1D-CNNs
B Hoppenstedt, M Reichert, G El-Khawaga, K Kammerer, KM Winter, ...
arXiv preprint arXiv:2004.14475, 2020
2020
Erstellung und Evaluierung eines Prototypen für OEE/PdM
B Hoppenstedt
Ulm University, 2016
2016
Image Segmentation To Locate Ancient Maya Architectures Using Deep Learning
J Landauer, B Hoppenstedt, J Allgaier
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Articles 1–20