Publikationen
Gefiltert nach:
Sortierung nach Jahr und AutorInnen
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., 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
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
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.
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
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.