Research Output per year
Research Output per year
Personal profile
Scientific Focus
The research interests of Thomas Kaester lie in the field of computer vision, pattern recognition, machine learning, image processing, and computer graphics. In particular, he is interested in:
- big data and analysis
- object detection, tracking and recognition
- human-machine interaction
- medical image processing
- action detection and classification in videos
- computer animation and visualization
- the design of intelligent / cgnitive vision systems
- image and video retrieval (including short-term and long-term learning)
- industrial image processing
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
Fingerprint
Dive into the research topics where Thomas Käster is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
Automated assessment of immunofixations with deep neural networks
Thiemann, C., Klitzke, B., Martinetz, P., Grüning, P., Käster, T., Barth, E., Kramer, J. & Martinetz, T., 01.10.2022, In: Journal of Laboratory Medicine. 46, 5, p. 331-336 6 p.Research output: Journal Articles › Journal articles › Research › peer-review
-
An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs
Mairhöfer, D., Laufer, M., Simon, P. M., Sieren, M., Bischof, A., Käster, T., Barth, E., Barkhausen, J. & Martinetz, T., 01.07.2021, Proceedings of the Fourth Conference on Medical Imaging with Deep Learning. Heinrich, M., Dou, Q., de Bruijne, M., Lellmann, J., Schläfer, A. & Ernst, F. (eds.). PMLR, Vol. 143. p. 484-496 13 p. (Proceedings of Machine Learning Research).Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review
-
Committees of deep feedforward networks trained with few data
Miclut, B., Kaester, T., Martinetz, T. & Barth, E., 23.06.2014, In: arXiv.org. 7 p.Research output: Journal Articles › Journal articles › Research
-
Key-point Detection with Multi-layer Center-surround Inhibition
Coleca, F., Zîrnovean, S., Käster, T., Martinetz, T. & Barth, E., 01.01.2014, Proceedings of the 9th International Conference on Computer Vision Theory and Application. Battiato, S. (ed.). 1 ed. Lisbon, Portugal: SciTePress, Vol. Vol. 1. p. 386-393 8 p. (INSTICC Conference Proceedings).Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review
-
How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series
Binder, T., Kriener, F., Wichner, C., Wille, M., Wellner, M., Kaester, T., Martinetz, T. & Barth, E., 09.03.2012, Human Vision and Electronic Imaging XVII. Rogowitz, B. E., Pappas, T. N. & de Ridder , H. (eds.). SPIE, Vol. 8291. p. 8291 - 8291 - 10 10 p. (Proceedings of SPIE; vol. 8291).Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review
Prizes
-
Innovationspreis 2012
Martinetz, T. (Award Recipient), Käster, T. (Award Recipient) & Fischer, S. (Award Recipient), 2012
Prize: Research Prizes, Scientific Awards