Publications

Krause & Kannen et al., (2025), Pro-adaptive Cognitive Assistive Technology: Concept and Application in Reading Support for ADHD.

Title Krause, A. F. *, Kannen, K. *, Büscher, S., Ressel, C. & Wild-Wall, N. (2025). Pro-adaptive Cognitive Assistive Technology: Concept and Application in Reading Support for ADHD. In International Conference on Extended Reality (pp. xx-xx). Springer Lecture Notes in Computer Science. (in press). (*) These authors contributed equally to this work.

Krause, A. F., Essig, K., Wild-Wall, N., Ressel, C. (2024), A proposal for the concept of Pro-adaptive Cognitive Assistive Technology. (Abstract HFES).

Title Krause, A. F., Essig, K., Wild-Wall, N., Ressel, C. (2024), A proposal for the concept of Pro-adaptive Cognitive Assistive Technology. Abstract, accepted at Human Factors and Ergonomics Societey Europe (HFES). Abstract Assistive Technology is becoming an integral part of our daily live, supporting people in different areas, for example while driving a car or cognitive demanding tasks at work or home. Yet, existing Assistive Technology often only considers the current situational context and capabilities of a user.

Wild-Wall et al., (2024), Strukturen zur Berücksichtigung ethischer Aspekte in der Entwicklung von digitalen assistiven Technologien für vulnerable Gruppen.

Title Nele Wild-Wall, Christian Ressel, Kyra Kannen, André Frank Krause, Sarah Büscher, Birgit Mosler und Barbara Arntz (2024), Strukturen zur Berücksichtigung ethischer Aspekte in der Entwicklung von digitalen assistiven Technologien für vulnerable Gruppen. (under review)

Krause, A. F., Ferger, A., Pitsch, K. (2023). Anonymization of Persons in Videos of Authentic Social Interaction: Model Selection and Parameter Optimization. In: 10th International Conference on CMC and Social Media Corpora for the Humanities (CMC-Corpora 2023), Mannheim.

Title Krause, A. F., Ferger, A., Pitsch, K. (2023). Anonymization of Persons in Videos of Authentic Social Interaction: Model Selection and Parameter Optimization. In: 10th International Conference on CMC and Social Media Corpora for the Humanities (CMC-Corpora 2023), Mannheim. Abstract Automatic anonymization of persons in video recordings requires robust detection of face and head areas. Machine learning-based face and posture detectors provide bounding boxes of face and head regions, but specific parameters need to be optimized to maximize the number of correctly anonymized persons and minimize manual annotation and verification efforts.

Ciuffo, B.. et al. (2023). Robotic Competitions to Design Future Transport Systems: The Case of JRC AUTOTRAC 2020.

Ciuffo, B., Makridis, M., Padovan, V., Benenati, E., Boriboonsomsin, K., Chembakasseril, M. T., Daras, P., Das, V., Dimou, A., Grammatico, S., Hartanto, R., Hoelscher, M., Jiang, Y., Krilasevic, S., Liu, S., Nguyen Le, Q. N., Rosier, C., Ruan, P., Wei, Z., … Zhao, Z. (2023). Robotic Competitions to Design Future Transport Systems: The Case of JRC AUTOTRAC 2020. Transportation Research Record, 2677(2), 1165–1178. https://doi.org/10.1177/03611981221110566{.broken_link}