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Patrick Zschech
Patrick Zschech
Professor for Intelligent Information Systems & Processes, Leipzig University
Verified email at uni-leipzig.de - Homepage
Title
Cited by
Cited by
Year
Machine learning and deep learning
C Janiesch, P Zschech, K Heinrich
Electronic Markets 31 (3), 685-695, 2021
17462021
Generative AI
S Feuerriegel, J Hartmann, C Janiesch, P Zschech
Business & Information Systems Engineering 66, 111–126, 2024
902024
A survey of image labelling for computer vision applications
C Sager, C Janiesch, P Zschech
Journal of Business Analytics 4 (2), 91-110, 2021
792021
Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning
K Heinrich, P Zschech, C Janiesch, M Bonin
Decision Support Systems, 113494, 2021
472021
How Much AI Do You Require? Decision Factors for Adopting AI Technology
J Wanner, K Heinrich, C Janiesch, P Zschech
41st International Conference on Information Systems (ICIS), India, 2020
45*2020
Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature
T Schoormann, G Strobel, F Möller, D Petrik, P Zschech
Communications of the Association for Information Systems 52 (1), 8, 2023
402023
White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems
J Wanner, LV Herm, K Heinrich, C Janiesch, P Zschech
41st International Conference on Information Systems (ICIS), India, 2020
382020
Machine Learning and Deep Learning. arXiv
C Janiesch, P Zschech, K Heinrich
34*2021
A Taxonomy of Recurring Data Analysis Problems in Maintenance Analytics
P Zschech
26th European Conference on Information Systems (ECIS), Portsmouth, UK, 2018
342018
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
J Zipfel, F Verworner, M Fischer, U Wieland, M Kraus, P Zschech
Computers & Industrial Engineering 177, 109045, 2023
302023
Intelligent User Assistance for Automated Data Mining Method Selection
P Zschech, R Horn, D Höschele, C Janiesch, K Heinrich
Business & Information Systems Engineering 62 (3), 227–247, 2020
30*2020
Prognostic Model Development with Missing Labels - A Condition-Based Maintenance Approach Using Machine Learning
P Zschech, K Heinrich, R Bink, JS Neufeld
Business & Information Systems Engineering 61 (3), 327–343, 2019
242019
Das aufstrebende Berufsbild des Data Scientist
C Schumann, P Zschech, A Hilbert
HMD Praxis der Wirtschaftsinformatik 53 (4), 453-466, 2016
222016
Everything Counts: A Taxonomy of Deep Learning Approaches for Object Counting
K Heinrich, A Roth, P Zschech
27th European Conference on Information Systems (ECIS), Stockholm, Schweden, 2019
212019
Predictive Maintenance in der industriellen Praxis
R Bink, P Zschech
HMD Praxis der Wirtschaftsinformatik: Vol. 55, No. 3, 2018
202018
labelcloud: A lightweight domain-independent labeling tool for 3d object detection in point clouds
C Sager, P Zschech, N Kühl
arXiv preprint arXiv:2103.04970, 2021
192021
Demystifying the Black Box: A Classification Scheme for Interpretation and Visualization of Deep Intelligent Systems
K Heinrich, P Zschech, T Skouti, J Griebenow, S Riechert
25th Americas Conference on Information Systems (AMCIS), 2019
182019
Data Science Skills and Enabling Enterprise Systems
P Zschech, V Fleißner, N Baumgärtel, A Hilbert
HMD Praxis der Wirtschaftsinformatik 55 (1), 163-181, 2018
182018
A picture is worth a collaboration: accumulating design knowledge for computer-vision-based hybrid intelligence systems
P Zschech, J Walk, K Heinrich, M Vössing, N Kühl
29th European Conference on Information Systems (ECIS), AIS Virtual Conference, 2021
172021
Towards a Taxonomic Benchmarking Framework for Predictive Maintenance: The Case of NASA’s Turbofan Degradation
P Zschech, J Bernien, K Heinrich
40th International Conference on Information Systems (ICIS), Munich, Germany, 2019
152019
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