Publikationen
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2021
Adensamer, A., & Klausner, L. D. (2021). “Part Man, Part Machine, All Cop”: Automation in Policing. Frontiers in Artificial Intelligence, 2021(4). https://doi.org/10/gk3q27
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2021). A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3–4), 1–42. https://doi.org/10/gnt2wf
Dumphart, B., Slijepčević, D., Unglaube, F., Kranzl, A., Baca, A., Zeppelzauer, M., & Horsak, B. (2021). An automated deep learning-based gait event detection algorithm for various pathologies. Gait & Posture, 90, 50–51. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.026
Eigner, O., Eresheim, S., Kieseberg, P., Klausner, L. D., Pirker, M., Priebe, T., Tjoa, S., Marulli, F., Mercaldo, F., & Priebe, T. (2021). Towards Resilient Artificial Intelligence: Survey and Research Issues. Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience, 536–542. https://doi.org/10.1109/CSR51186.2021.9527986
Hogan, A., Blomqvist, E., Cochez, M., d"Amato, C., de Melo, G., Gutierrez, C., Gayo, J. E. L., Kirrane, S., Neumaier, S., Polleres, A., Navigli, R., Ngomo, A.-C. N., Rashid, S. M., Rula, A., Schmelzeisen, L., Sequeda, J., Staab, S., & Zimmermann, A. (2021). Knowledge Graphs. ACM Computing Surveys, 54(4), 1–37. https://doi.org/10.1145/3447772
Holzinger, A., Weippl, E., Tjoa, A. M., & Kieseberg, P. (2021). Digital Transformation for Sustainable Development Goals (SDGs) - A Security, Safety and Privacy Perspective on AI. In A. Holzinger, P. Kieseberg, A. M. Tjoa, & E. Weippl (Eds.), Machine Learning and Knowledge Extraction (pp. 1–20). Springer International Publishing.
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2021). 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021 Virtual Event, August 17–20, 2021 Proceedings. Springer. https://link.springer.com/book/10.1007/978-3-030-84060-0?utm_medium=referral&utm_source=google_books&utm_campaign=3_pier05_buy_print&utm_content=en_08082017
Iber, M., Dumphart, B., Oliveira, V. A. de. J., Ferstl, S., Reis, J., Slijepcevic, D., Heller, M., Raberger, A.-M., & Horsak, B. (2021). Mind the Steps: Towards Auditory Feedback in Tele-Rehabilitation Based on Automated Gait Classification. In Proceedings of the 16th International Audio Mostly Conference (AM"21). Audio Mostly 2021. https://doi.org/10/gnt2tc
Kieseberg, P., Schrittwieser, S., & Weippl, E. (2021). Secure Internal Data Markets. Future Internet, 13(8). https://doi.org/https://doi.org/10.3390/fi13080208
Krondorfer, P., Slijepčević, D., Unglaube, F., Kranzl, A., Breiteneder, C., Zeppelzauer, M., & Horsak, B. (2021). Deep learning-based similarity retrieval in clinical 3D gait analysis. Gait & Posture, 90, 127–128. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.066
Pellegrini, T., Beraha, D., Gladyshev, M., de Grosbois, J., Hakopov, Z., Jehadeesan, R., Markov, A., Marmonti, E., & Nenadic, G. (2021). Exploring Semantic Technologies and Their Application to Nuclear Knowledge Management. INTERNATIONAL ATOMIC ENERGY AGENCY. https://www.iaea.org/publications/13469/exploring-semantic-technologies-and-their-application-to-nuclear-knowledge-management
Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19. https://doi.org/10.1016/j.cose.2021.102488
Stöger, K., Schneeberger, D., Kieseberg, P., & Holzinger, A. (2021). Legal aspects of data cleansing in medical AI. Computer Law & Security Review, 42. https://doi.org/https://doi.org/10.1016/j.clsr.2021.105587
Zielinski, B., Lipinski, M., Juda, M., Zeppelzauer, Matthias, & Dlotko, Pawel. (2021). Persistence Codebooks for Topological Data Analysis. Journal of Artificial Intelligence Review, 54, 1969–2009. https://doi.org/https://doi.org/10.1007/s10462-020-09897-4
2020
Holzinger, A., Kieseberg, P., & Müller, H. (2020). KANDINSKY Patterns: A Swiss-Knife for the Study of Explainable AI. ERCIM-News, 120, 41–42. https://phaidra.fhstp.ac.at/o:4336
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2020). Machine Learning and Knowledge Extraction: Fourth IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2020. Springer. https://link.springer.com/book/10.1007/978-3-030-57321-8
Horsak, B., Slijepcevic, D., Raberger, A.-M., Schwab, C., Worisch, M., & Zeppelzauer, M. (2020). GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait. Scientific Data, 7:143(1), 1–8. https://doi.org/10/gh372d
Horsak, B., Dumphart, B., Slijepcevic, D., & Zeppelzauer, M. (2020). Explainable Artificial Intelligence (XAI) und ihre Anwendung auf Klassifikationsprobleme in der Ganganalyse. Abstractband Des 3. GAMMA Kongress. 3. GAMMA Kongress, München, Deutschland.
Horst, F., Slijepcevic, D., Zeppelzauer, M., Raberger, A. M., Lapuschkin, S., Samek, W., Schöllhorn, W. I., Breiteneder, C., & Horsak, B. (2020). Explaining automated gender classification of human gait. Gait & Posture, 81, supplement 1, 159–160. https://doi.org/10/ghr9k6
Longo, L., Goebel, R., Lecue, F., Kieseberg, P., & Holzinger, A. (2020, August 27). Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions. International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Virtuell.