Alexander Diete
Credit: Emilie Orgler
Researcher
alexinformatik.uni-mannheim.de
B6, 26, Room C 1.07
Publications
- Diete, A., Sztyler, T. and Stuckenschmidt, H. (2019). Vision and acceleration modalities: Partners for recognizing complex activities. In , 2019 IEEE International Conference on Pervasive Computing and Communications workshops (PerCom workshops) : took place 11–15 March 2019 in Kyoto, Japan (S. 101–106). , IEEE Computer Society: Piscataway, NJ.
- Diete, A., Sztyler, T., Weiland, L. and Stuckenschmidt, H. (2018). Improving motion-based activity recognition with ego-centric vision. In , 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 : Athens, Greece, March 19–23, 2018 (S. 448–491). , IEEE Computer Society: Piscataway, NJ.
- Diete, A., Sztyler, T. and Stuckenschmidt, H. (2017). A smart data annotation tool for multi-sensor activity recognition. In , 2017 IEEE International Conference on Pervasive Computing and Communications Workshops : PERCOM Workshops (S. 111–116). , IEEE Computer Soc.: Piscataway, NJ.
- Diete, A., Sztyler, T., Weiland, L. and Stuckenschmidt, H. (2017). Recognizing grabbing actions from inertial and video sensor data in a warehouse scenario. In , 14th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2017) / 12th International Conference on Future Networks and Communications (FNC 2017) / Affiliated Workshops (S. 16–23). Procedia computer science, Elsevier: Amsterdam [u.a.].
- Diete, A., Sztyler, T., Weiland, L. and Stuckenschmidt, H. (2016). Exploring a multi-sensor picking process in the future warehouse.
In , UbiComp/
ISWC'16 Adjunct : Adjunct proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers (S. 1755-1758). , ACM: New York, NY.
- Diete, A. and Stuckenschmidt, H. (2019). Fusing object information and inertial data for activity recognition. Sensors, 19, 4119, 1–22.
- Diete, A., Sztyler, T. and Stuckenschmidt, H. (2018). Exploring semi-supervised methods for labeling support in multimodal datasets. Sensors, 18, Article 2639.
- Diete, A. (2021). Towards multimodal activity recognition in complex scenarios. Dissertation. Mannheim.