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6 Publications


2023 | Conference Paper | LibreCat-ID: 52816
Gräßler, I., & Hieb, M. (2023). Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. Lectures, 253–524. https://doi.org/10.5162/smsi2023/d7.4
LibreCat | DOI
 

2021 | Journal Article | LibreCat-ID: 20212 | OA
Prester, J., Wagner, G., Schryen, G., & Hassan, N. R. (2021). Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach. Decision Support Systems, 140(January), Article 113432.
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2021 | Conference Paper | LibreCat-ID: 24547
Müller, O., Caron, M., Döring, M., Heuwinkel, T., & Baumeister, J. (n.d.). PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data. 8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021). European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2021), Online.
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2020 | Conference Paper | LibreCat-ID: 19609 | OA
Schneider, S. B., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., Khalili, R., & Hecker, A. (2020). Self-Driving Network and Service Coordination Using Deep Reinforcement Learning. In IEEE International Conference on Network and Service Management (CNSM). IEEE.
LibreCat | Files available
 

2020 | Conference Paper | LibreCat-ID: 15580
Kersting, J., & Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400). Setúbal, Portugal: SCITEPRESS.
LibreCat | Files available
 

2020 | Conference Paper | LibreCat-ID: 48897
Seiler, M., Pohl, J., Bossek, J., Kerschke, P., & Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. Parallel Problem Solving from {Nature} (PPSN XVI), 48–64. https://doi.org/10.1007/978-3-030-58112-1_4
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