Elmar Rückert
Research output
- 2021
- Published
A novel chlorophyll fluorescence-based approach for mowing area classification
Rottmann, N., Bruder, R., Schweikard, A. & Rückert, E., 15 Feb 2021, In: IEEE sensors journal. 21, 4, p. 4500-4508 9 p., 9234496.Research output: Contribution to journal › Article › Research › peer-review
- Published
KI 2021: Advances in Artificial Intelligence - Preface
Edelkamp, S., Möller, R. & Rückert, E., 2021, KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI, Virtual Event, September 27 – October 1, 2021, Proceedings. Edelkamp, S., Möller, R. & Rückert, E. (eds.). Vol. 12873 LNAI. p. v-vi (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- 2020
- Published
Evolutionary training and abstraction yields algorithmic generalization of neural computers
Tanneberg, D., Rückert, E. & Peters, J., 16 Nov 2020, In: Nature machine intelligence.Research output: Contribution to journal › Article › Research › peer-review
- Published
Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors
Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., 25 Oct 2020.Research output: Contribution to conference › Paper › peer-review
- Published
Learning hierarchical acquisition functions for bayesian optimization
Rottmann, N., Kunavar, T., Babic, J., Peters, J. & Rueckert, E., 24 Oct 2020, IEEE International Conference on Intelligent Robots and Systems. p. 5490-5496 7 p. (IEEE International Conference on Intelligent Robots and Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates
Çallar, T. C., Rueckert, E. & Böttger, S., 1 Sept 2020, In: Current directions in biomedical engineering. 6.2020, 3, 4 p., 20203031.Research output: Contribution to journal › Article › Research › peer-review
Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control
Rückert, E., Čamernik, J., Peters, J. & Babič, J., 16 Apr 2020, In: Scientific reports. 6.2016, 1, 12 p., 28455 / 6694.Research output: Contribution to journal › Article › Research › peer-review
- 2019
- Published
Experience Reuse with Probabilistic Movement Primitives
Stark, S., Peters, J. & Rueckert, E., Nov 2019, IEEE International Conference on Intelligent Robots and Systems. p. 1210-1217 8 p. (IEEE International Conference on Intelligent Robots and Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Medical robotics simulation framework for application-specific optimal kinematics
Böttger, S., Çallar, T. C., Schweikard, A. & Rückert, E., 18 Sept 2019, In: Current directions in biomedical engineering. 5.2019, 1, p. 145-148 4 p.Research output: Contribution to journal › Article › Research › peer-review
- Published
Loop closure detection in closed environments
Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., Sept 2019.Research output: Contribution to conference › Paper › peer-review
