Successful Graduation of Daniel Tanneberg
Congratulations to Daniel Tanneberg for completing his PhD. He is the first graduate of Prof. Elmar Rueckert’s group.
Journal Paper accepted at IEEE Sensors Journal
Nils Rottmann, Ralf Bruder, Achim Schweikard, Elmar Rueckert
A novel Chlorophyll Fluorescence based approach for Mowing Area Classification
accepted (Oct, 12th 2020) at IEEE Sensors Journal with an Impact Factor of 3 (2019).
Conference Paper Accepted at IEEE Sensors
The paper by Nils Rottmann, Ralf Burder, Achim Schweikard und Elmar Rueckert on Exploiting Chlorophyll Fluorescense for Building Robust low-Cost Mowing Area Detectors was accepted for publication at the IEEE SENSORS 2020 Conference, to be held from October 25-28, 2020.
Conference Paper accepted at BMT2020
The paper by Tolga-Can Çallar, Elmar Rueckert and Sven Böttger on “Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates” was accepted for publication in the 54th Annual Conference of the German Society for Biomedical Engineering (BMT 2020).
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Workshop accepted at IROS 2020
Our workshop on „New Horizons for Robot Learning“ was accepted at the International Conference on Intelligent Robots and Systems (IROS’ 2020). See https://iros.ai-lab.science
Conference Paper accepted at IROS 2020
The paper by Nils Rottmann, Tjaša Kunavar, Jan Babič, Jan Peters and Elmar Rueckert on “Learning Hierarchical Acquisition Functions for Bayesian Optimization” was accepted for publication at the International Conference on Intelligent Robots and Systems (IROS’ 2020).
Proceedings of Machine Learning Research Paper accepted
E. Cartoni, F. Mannella, V.G. Santucci, J. Triesch, E. Rueckert, G. Baldassarre. REAL-2019: Robot open-Ended Autonomous Learning competition. Proceedings of Machine Learning Research 123:142-152, 2020. NeurIPS 2019 Competition and Demonstration Track
Conference Paper accepted at ASPAI 2020
The paper by Honghu Xue, Sven Boettger, Nils Rottmann, Harit Pandya, Ralf Bruder, Gerhard Neumann, Achim Schweikard and Elmar Rueckert on “Sample-Efficient Covariance Matrix Adaptation Evolutional Strategy via Simulated Rollouts in Neural Networks” was accepted for publication at the 2nd International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI’ 2020).
Successful grant: DFG project with > 650kEURO granted
Together with Prof. Philipp Beckerle from the TU Dortmund, we got our research project on ‘Active transfer learning with neural networks through human-robot interactions’ granted.
Winner of the ’German AI-Young Research Price 2019’
Prof. Rueckert won the ’German AI-Young Researcher Price 2019’ (germ. deutscher KI-Nachwuchspreis 2019) by Bilanz & McKinsey – KI-Denker der Zukunft. The awards ceremony was on Sept. 26th, 2019. The main AI price was given to Prof. Kristian Kersting from the TU-Darmstadt. The german company DeepL received the award for applied AI.
