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ORCIDDan Hudson 0001
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- affiliation: Osnabrück University, Semantic Information Systems Group, Germany
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2020 – today
- 2026
[j3]Dan Hudson
, Jurgen van den Hoogen, Martin Atzmueller:
Finding One's Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector. IEEE Access 14: 39094-39119 (2026)- [j2]Jurgen van den Hoogen, Dan Hudson, Martin Atzmueller:
A comparison of graph construction techniques for applying graph signal processing to soil moisture networks. Discov. Comput. 29(1): 17 (2026) - 2024
- [j1]Jurgen van den Hoogen, Dan Hudson, Stefan Bloemheuvel, Martin Atzmueller:
Hyperparameter analysis of wide-kernel CNN architectures in industrial fault detection: an exploratory study. Int. J. Data Sci. Anal. 18(4): 423-444 (2024) - [c11]Jurgen van den Hoogen, Dan Hudson, Martin Atzmueller:
Data-Hungry Fault Detection Algorithms Can Try Transfer Learning for Starters. ICDEW 2024: 91-95 - [c10]Jurgen van den Hoogen, Dan Hudson, Martin Atzmueller:
Graph Signal Processing Unearths the Best Locations for Soil Moisture Sensors. ICMLA 2024: 963-968 - [c9]Dan Hudson, Jurgen van den Hoogen, Stefan Bloemheuvel, Martin Atzmueller:
Stay Tuned! Analysing Hyperparameters of a Wide-Kernel Architecture for Industrial Faults. CAI 2024: 1350-1356 - [i3]Dan Hudson, Jurgen van den Hoogen, Martin Atzmueller:
Tailoring the Hyperparameters of a Wide-Kernel Convolutional Neural Network to Fit Different Bearing Fault Vibration Datasets. CoRR abs/2411.15191 (2024) - 2023
- [c8]Jurgen van den Hoogen, Dan Hudson, Stefan Bloemheuvel, Martin Atzmueller:
Hyperparameter Analysis of Wide-Kernel CNN Architectures in Industrial Fault Detection - An Exploratory Study. DSAA 2023: 1-2 - [c7]Maciej Szelazek, Dan Hudson, Szymon Bobek, Grzegorz J. Nalepa, Martin Atzmueller:
Enhanced Explanations for Knowledge-Augmented Clustering using Subgroup Discovery. DSAA 2023: 1-11 - [c6]Dan Hudson, Martin Atzmueller:
Subgroup Discovery with SD4Py. ECAI Workshops (1) 2023: 338-348 - [c5]Dan Hudson, Ruud J. R. Den Hartigh, L. Rens A. Meerhoff, Martin Atzmueller:
Explainable Multi-Modal and Local Approaches to Modelling Injuries in Sports Data. ICDM (Workshops) 2023: 949-957 - 2022
- [c4]Dan Hudson, Travis J. Wiltshire, Martin Atzmueller:
Visualization Methods for Exploratory Subgroup Discovery on Time Series Data. IWINAC (1) 2022: 34-44 - 2021
- [c3]Dan Hudson, Travis J. Wiltshire, Martin Atzmueller:
Local Exceptionality Detection in Time Series Using Subgroup Discovery: An Approach Exemplified on Team Interaction Data. DS 2021: 435-445 - [c2]Travis J. Wiltshire, Dan Hudson, Max Belitsky, Philia Lijdsman, Stijn Wever, Martin Atzmueller:
Examining Team Interaction using Dynamic Complexity and Network Visualizations. ICHMS 2021: 1-6 - [c1]Ngoc N. T. Doan, Dan Hudson, Travis J. Wiltshire, Philia Lijdsman, Stijn Wever, Martin Atzmueller:
Human Interaction and Networking Transitions System (HINTS) for Social User Analytics and Modeling of Offline Team Group Interaction Information. UMAP (Adjunct Publication) 2021: 71-74 - [i2]Dan Hudson, Travis J. Wiltshire, Martin Atzmueller:
Local Exceptionality Detection in Time Series Using Subgroup Discovery. CoRR abs/2108.11751 (2021) - 2020
- [i1]Travis J. Wiltshire, Dan Hudson, Philia Lijdsman, Stijn Wever, Martin Atzmueller:
Social Analytics of Team Interaction using Dynamic Complexity Heat Maps and Network Visualizations. CoRR abs/2009.04445 (2020)
Coauthor Index
aka: Martin Atzmueller
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