A2D2: Audi autonomous driving dataset J Geyer, Y Kassahun, M Mahmudi, X Ricou, R Durgesh, AS Chung, ... arXiv preprint arXiv:2004.06320, 2020 | 419 | 2020 |
Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions Y Kassahun, B Yu, AT Tibebu, D Stoyanov, S Giannarou, JH Metzen, ... International journal of computer assisted radiology and surgery 11, 553-568, 2016 | 253 | 2016 |
Efficient reinforcement learning through Evolutionary Acquisition of Neural Topologies. Y Kassahun, G Sommer ESANN, 259-266, 2005 | 98 | 2005 |
Automatic classification of epilepsy types using ontology-based and genetics-based machine learning Y Kassahun, R Perrone, E De Momi, E Berghöfer, L Tassi, MP Canevini, ... Artificial intelligence in medicine 61 (2), 79-88, 2014 | 74 | 2014 |
A2D2: AEV autonomous driving dataset J Geyer, Y Kassahun, M Mahmudi, X Ricou, R Durgesh, AS Chung, ... arXiv preprint arXiv:2004.06320, 2019 | 40 | 2019 |
A2d2: Audi autonomous driving dataset. arXiv 2020 J Geyer, Y Kassahun, M Mahmudi, X Ricou, R Durgesh, AS Chung, ... arXiv preprint arXiv:2004.06320, 2004 | 39 | 2004 |
A common genetic encoding for both direct and indirect encodings of networks Y Kassahun, M Edgington, JH Metzen, G Sommer, F Kirchner Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 33 | 2007 |
Learning neural networks for visual servoing using evolutionary methods NT Siebel, Y Kassahun 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06), 6-6, 2006 | 28 | 2006 |
Towards a unified approach to learning and adaptation Y Kassahun | 26 | 2006 |
Analysis of an evolutionary reinforcement learning method in a multiagent domain JH Metzen, M Edgington, Y Kassahun, F Kirchner Proceedings of the 7th international joint conference on Autonomous agents …, 2008 | 24 | 2008 |
Learning in compressed space A Fabisch, Y Kassahun, H Wöhrle, F Kirchner Neural networks 42, 83-93, 2013 | 18 | 2013 |
Experimental robot inverse dynamics identification using classical and machine learning techniques V Bargsten, J de Gea Fernandez, Y Kassahun Proceedings of ISR 2016: 47st International Symposium on Robotics, 1-6, 2016 | 17 | 2016 |
Accelerating neuroevolutionary methods using a Kalman filter Y Kassahun, J de Gea, M Edgington, JH Metzen, F Kirchner Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008 | 11 | 2008 |
Performance evaluation of EANT in the robocup keepaway benchmark JH Metzen, M Edgington, Y Kassahun, F Kirchner Sixth International Conference on Machine Learning and Applications (ICMLA …, 2007 | 11 | 2007 |
Dynamic motion modelling for legged robots M Edgington, Y Kassahun, F Kirchner 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2009 | 9 | 2009 |
Evolution of neural networks through incremental acquisition of neural structures Y Kassahun, G Sommer | 9 | 2005 |
Cognitive autonomous catheters operating in dynamic environments E Vander Poorten, P Tran, A Devreker, C Gruijthuijsen, S Portoles-Diez, ... Journal of Medical Robotics Research 1 (03), 1640011, 2016 | 8 | 2016 |
Learning catheter-aorta interaction model using joint probability densities Y Kassahun, B Yu, E Vander Poorten Proceedings of the 3rd joint workshop on new technologies for computer/robot …, 2013 | 8 | 2013 |
Learning the elasticity of a series-elastic actuator for accurate torque control B Yu, J de Gea Fernández, Y Kassahun, V Bargsten Advances in Artificial Intelligence: From Theory to Practice: 30th …, 2017 | 7 | 2017 |
Learning walking patterns for kinematically complex robots using evolution strategies M Römmermann, M Edgington, JH Metzen, J de Gea, Y Kassahun, ... Parallel Problem Solving from Nature–PPSN X: 10th International Conference …, 2008 | 7 | 2008 |