Frederic T. Stahl
Orcid: 0000-0002-4860-0203Affiliations:
- German Research Center for Artificial Intelligence, Oldenburg, Germany
- University of Reading, School of Systems Engineering (former)
According to our database1,
Frederic T. Stahl
authored at least 73 papers
between 2005 and 2024.
Collaborative distances:
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Bibliography
2024
Human-Robot Collaboration System Setup for Weed Harvesting Scenarios in Aquatic Lakes.
CoRR, 2024
On the Development of a Pixel-Wise Plastic Waste Identification System for Multispectral Remote Sensing Applications.
Proceedings of the Artificial Intelligence XLI, 2024
Proceedings of the Artificial Intelligence XLI, 2024
Model Generalisation For Predicting The Amount Of Photosynthetically Available Radiation In The Water Column From Freefall Profiler Observations.
Proceedings of the 38th ECMS International Conference on Modelling and Simulation, 2024
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024
2023
Proceedings of the Artificial Intelligence XL, 2023
On Reproducible Implementations in Unsupervised Concept Drift Detection Algorithms Research.
Proceedings of the Artificial Intelligence XL, 2023
2022
IEEE Access, 2022
Multi-Phase Algorithmic Framework to Prevent SQL Injection Attacks using Improved Machine learning and Deep learning to Enhance Database security in Real-time.
Proceedings of the 15th International Conference on Security of Information and Networks, 2022
On an Artificial Neural Network Approach for Predicting Photosynthetically Active Radiation in the Water Column.
Proceedings of the Artificial Intelligence XXXIX, 2022
Explainable Boosting Machines for Network Intrusion Detection with Features Reduction.
Proceedings of the Artificial Intelligence XXXIX, 2022
Proceedings of the Artificial Intelligence XXXIX, 2022
Road Intersection Coordination Scheme for Mixed Traffic (Human Driven and Driver-Less Vehicles): A Systematic Review.
Proceedings of the Intelligent Computing, 2022
Proceedings of the Intelligent Computing, 2022
A Model For Predicting The Amount Of Photosynthetically Available Radiation From BGC-ARGO Float Observations In The Water Column.
Proceedings of the 36th ECMS International Conference on Modelling and Simulation, 2022
2021
Inf., 2021
Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams.
IEEE Access, 2021
IEEE Access, 2021
Proceedings of the Artificial Intelligence XXXVIII, 2021
Proceedings of the 35th International ECMS International Conference on Modelling and Simulation, 2021
2020
Knowl. Based Syst., 2020
2019
A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
2018
Real-time feature selection technique with concept drift detection using adaptive micro-clusters for data stream mining.
Knowl. Based Syst., 2018
A Rule-Based Classifier with Accurate and Fast Rule Term Induction for Continuous Attributes.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018
Building Adaptive Data Mining Models on Streaming Data in Real-Time, an Outlook on Challenges, Approaches and Ongoing Research.
Proceedings of the European Conference on Modelling and Simulation, 2018
2017
On expressiveness and uncertainty awareness in rule-based classification for data streams.
Neurocomputing, 2017
Future Gener. Comput. Syst., 2017
Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries.
Proceedings of the Artificial Intelligence XXXIV, 2017
2016
A rule dynamics approach to event detection in Twitter with its application to sports and politics.
Expert Syst. Appl., 2016
A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network.
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016
A Statistical Learning Method to Fast Generalised Rule Induction Directly from Raw Measurements.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016
Towards Online Concept Drift Detection with Feature Selection for Data Stream Classification.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016
2015
Trans. Large Scale Data Knowl. Centered Syst., 2015
Neurocomputing, 2015
Proceedings of the Research and Development in Intelligent Systems XXXII, 2015
Proceedings of the Internet and Distributed Computing Systems, 2015
Proceedings of the Internet and Distributed Computing Systems, 2015
2014
Data stream mining in ubiquitous environments: state-of-the-art and current directions.
WIREs Data Mining Knowl. Discov., 2014
J. Data Min. Digit. Humanit., 2014
Expert Syst. J. Knowl. Eng., 2014
Towards a Parallel Computationally Efficient Approach to Scaling Up Data Stream Classification.
Proceedings of the Research and Development in Intelligent Systems XXXI, 2014
Proceedings of the Research and Development in Intelligent Systems XXXI, 2014
Extraction of Unexpected Rules from Twitter Hashtags and its Application to Sport Events.
Proceedings of the 13th International Conference on Machine Learning and Applications, 2014
Proceedings of the Engineering Applications of Neural Networks, 2014
2013
WIREs Data Mining Knowl. Discov., 2013
Knowl. Eng. Rev., 2013
Proceedings of the Research and Development in Intelligent Systems XXX, 2013
Proceedings of the Research and Development in Intelligent Systems XXX, 2013
Proceedings of the Artificial Intelligence and Soft Computing, 2013
2012
WIREs Data Mining Knowl. Discov., 2012
Trans. Large Scale Data Knowl. Centered Syst., 2012
Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks.
Knowl. Based Syst., 2012
Jmax-pruning: A facility for the information theoretic pruning of modular classification rules.
Knowl. Based Syst., 2012
Parallel Random Prism: A Computationally Efficient Ensemble Learner for Classification.
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012
Proceedings of the Research and Development in Intelligent Systems XXIX, 2012
2011
Proceedings of the Research and Development in Intelligent Systems XXVIII, 2011
Proceedings of the Foundations of Intelligent Systems - 19th International Symposium, 2011
Proceedings of the 2011 International Conference on High Performance Computing & Simulation, 2011
2010
P-found: Grid-enabling distributed repositories of protein folding and unfolding simulations for data mining.
Future Gener. Comput. Syst., 2010
Proceedings of the Research and Development in Intelligent Systems XXVII, 2010
Proceedings of the Artificial Intelligence in Theory and Practice III, 2010
Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments.
Proceedings of the 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010
2009
Proceedings of the Research and Development in Intelligent Systems XXVI, 2009
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009
2008
Proceedings of the Research and Development in Intelligent Systems XXV, 2008
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction.
Proceedings of the Artificial Intelligence in Theory and Practice II, 2008
Grid Computing Solutions for Distributed Repositories of Protein Folding and Unfolding Simulations.
Proceedings of the Computational Science, 2008
2007
Towards a Computationally Efficient Approach to Modular Classification Rule Induction.
Proceedings of the Research and Development in Intelligent Systems XXIV, 2007
2005
Proceedings of the 5th International Symposium on Cluster Computing and the Grid (CCGrid 2005), 2005