Software Technologie und Anwendungen Research Center Hagenberg
Publikationen
An integrated approach for power transformer modeling and manufacturing
C. Lettner, M. Moser, J. Pichler - An integrated approach for power transformer modeling and manufacturing - International Conference on Industry 4.0 and Smart Manufacturing, Linz, Österreich, 2020, pp. 351-355
Stepwise abstraction of high-level system specifications from source code
F. Ferrarotti, M. Moser, J. Pichler - Stepwise abstraction of high-level system specifications from source code - Journal of Computer Languages, 2020
Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets
G. Zwettler, D. Holmes III, W. Backfrieder - Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets - Proceedings of the WSCG 2020, Pilsen, Tschechische Republik, 2020, pp. 10
Hybrid Approach for Orientation-Estimation of Rotating Humans in Video Frames Acquired by Stationary Monocular Camera
D. Baumgartner, C. Praschl, T. Zucali, G. Zwettler - Hybrid Approach for Orientation-Estimation of Rotating Humans in Video Frames Acquired by Stationary Monocular Camera - Proceedings of the WSCG 2020, Pilsen, Tschechische Republik, 2020, pp. 9
The precise orientation-estimation of humans relative to the POSE of a monocular camera system is a challenging task due to the general aspects of camera…
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Supporting Teamwork in Industrial Virtual Reality Applications
J. Wolfartsberger, J. Zenisek, N. Wild - Supporting Teamwork in Industrial Virtual Reality Applications - Procedia Manufacturing, 2020, pp. 2-7
Virtual Reality (VR) systems allow for novel modes of visualization and interaction to support engineering design reviews. However, there are still research…
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Effects of Arrival Uncertainty on Solver Performance in Dynamic Stacking Problems
S. Raggl, A. Beham, S. Wagner, M. Affenzeller - Effects of Arrival Uncertainty on Solver Performance in Dynamic Stacking Problems - Proceedings of the 32nd European Modeling & Simulation Symposium (EMSS 2020), Online, Griechenland, 2020, pp. 193-200
Urheberrechtliche Relevanz von KI-generierten sowie verschlüsselten Inhalten
P. Burgstaller, E. Hermann - Urheberrechtliche Relevanz von KI-generierten sowie verschlüsselten Inhalten - Österreichsiche Blätter für gewerblichen Rechtsschutz und Urheberrecht, 2020
Der Einsatz von künstlich intelligenten (KI) Systemen tangiert beinahe alle Rechtsbereiche – vom Arbeits- und Datenschutzrecht über das Gesundheits- und Pflege…
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Using Deep Learning for Depth Estimation and 3D Reconstruction of Humans
A. Freller, G. Zwettler - Using Deep Learning for Depth Estimation and 3D Reconstruction of Humans - Proceedings of the 32th EUROPEAN MODELING AND SIMULATION SYMPOSIUM, Athen, Griechenland, 2020, pp. 6
Deep learning depth estimation from monocular video feed is a common strategy to get rough 3D surface information when
an RGB-D camera is not present. Depth…
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Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles
A. Schuler, G. Anderst-Kotsis - Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles - 2020 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Bari, Italien, 2020
Background: Third-party software libraries often serve as fundamental building blocks for developing applications. However, depending on such libraries for…
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Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains
G. Zwettler, D. Holmes III, W. Backfrieder - Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains - Proceedings of the VISAPP 2020, Valetta, Malta, 2020, pp. 66-78
MS Annika: A New Search Tool for the Identification of Cross-Linked Peptides from Tandem Mass Spectrometry Data
G. J. Pirklbauer, C. Stieger, S. M. Winkler, K. Mechtler, V. Dorfer - MS Annika: A New Search Tool for the Identification of Cross-Linked Peptides from Tandem Mass Spectrometry Data - Proceedings of the 9th Symposium on Structural Proteomics (SSP2019), Göttingen, Deutschland, 2019
Numerous chemical cross-linkers linkers have been developed over the last years, each with their own physical and chemical properties [1]. The development of…
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Parameter identification for symbolic regression using nonlinear least squares
M. Kommenda, B. Burlacu, G. K. Kronberger, M. Affenzeller - Parameter identification for symbolic regression using nonlinear least squares - Genetic Programming and Evolvable Machines, 2019, pp. 471-501
In this paper we analyze the effects of using nonlinear least squares for parameter identification of symbolic regression models and integrate it as local…
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Using Ontologies to Express Prior Knowledge for Genetic Programming
S. Prieschl, D. Girardi, G. K. Kronberger - Using Ontologies to Express Prior Knowledge for Genetic Programming - Machine Learning and Knowledge Extraction. CD-MAKE 2019., Canterbury, Vereinigtes Königreich von Großbritannien und Nordirland, 2019, pp. 362-376
Ontologies are useful for modeling domains and can be used to capture expert knowledge about a system. Genetic programming can be used to identify statistical…
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A Cost Optimized Data Acquisition System For Predictive Maintenance
E. Strumpf, F. Holzinger, F. Eibensteiner, J. Langer - A Cost Optimized Data Acquisition System For Predictive Maintenance - 6. Tagung Innovation Messtechnik, Linz, Österreich, 2019, pp. 104-108
Preprocessing and Modeling of Radial Fan Data for Health State Prediction
F. Holzinger, M. Kommenda - Preprocessing and Modeling of Radial Fan Data for Health State Prediction - Computer Aided Systems Theory – EUROCAST 2019, Las Palmas, Gran Canaria, Spanien, 2019
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
W. Roland, M. Kommenda, C. Marschik, J. Miethlinger - Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion - Polymers, Vol. 11, No. 2, 2019
Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for…
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New Approaches for Equalizing the Granulate Size and Bulk Density in Mechanical Recycling Using Heuristic Approaches Based on Specific Data Analyses
M. Aigner, L. Kammerer, F. Schieder, G. K. Kronberger - New Approaches for Equalizing the Granulate Size and Bulk Density in Mechanical Recycling Using Heuristic Approaches Based on Specific Data Analyses - Proceedings of SPE ANTEC 2019, Detroit, Vereinigte Staaten von Amerika, 2019, pp. 1-7
Exactly defined and constant granulates become more and more important in recycling business. The material is very often mixed with virgin granulate, sold on…
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Analyzing the potential of Virtual Reality for engineering design review
J. Wolfartsberger - Analyzing the potential of Virtual Reality for engineering design review - Automation in Construction, 2019, pp. 27-37
Integration of Physical Knowledge in Empirical Models - A New Approach to Regression Analysis
G. K. Kronberger, S. Scheidel, C. Haider, M. Kommenda, M. Kordon - Integration of Physical Knowledge in Empirical Models - A New Approach to Regression Analysis - 8th International Symposium on Development Methodology, Wiesbaden, Deutschland, 2019, pp. 1-9
Design of experiments, empirical modelling and model-based optimization is a widely known and approved approach for high-dimensional optimization problems in…
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Extracting High-Level System Specifications from Source Code via Abstract State Machines
F. Ferrarotti, J. Pichler, M. Moser, G. Buchgeher - Extracting High-Level System Specifications from Source Code via Abstract State Machines - International Conference on Model and Data Engineering, Tuolouse, France, Frankreich, 2019, pp. 267-283
Understanding and Preparing Data of Industrial Processes for Machine Learning Applications
P. Fleck, M. Kügel, M. Kommenda - Understanding and Preparing Data of Industrial Processes for Machine Learning Applications - Computer Aided Systems Theory – EUROCAST 2019, Las Palmas, Gran Canaria, Spanien, 2019
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