Heiko Wersing

heiko.wersing@honda-ri.de
PEVZ-ID
54878447

51 Publikationen

Alle markieren

  • [51]
    2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2993477
    Beierling, H.; Richter, P.; Brandt, M.; Terfloth, L.; Schulte, C.; Wersing, H.; Vollmer, A. - L. (2024): What you need to know about a learning robot: Identifying the enabling architecture of complex systems Cognitive Systems Research,88:101286
    PUB | DOI | Download (ext.) | WoS
     
  • [50]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959418
    Göpfert, J. P.; Kuhl, U.; Hindemith, L.; Wersing, H.; Hammer, B. (2021): Intuitiveness in Active Teaching IEEE Transactions on Human-Machine Systems, 1-10.
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  • [49]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2950092
    Limberg, C.; Wersing, H.; Ritter, H. (2020): Beyond Cross-Validation—Accuracy Estimation for Incremental and Active Learning Models Machine Learning and Knowledge Extraction,2:(3): 327-346.
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  • [48]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950093
    Limberg, C.; Wersing, H.; Ritter, H. (2020): Accuracy Estimation for an Incrementally Learning Cooperative Inventory Assistant Robot. In: Haiqin Yang; Kitsuchart Pasupa; Andrew Chi-Sing Leung; James T. Kwok; Jonathan H. Chan; Irwin King (Hrsg.): Neural Information Processing. 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part II. Cham: Springer International Publishing. (Lecture Notes in Computer Science, 12533). S. 738-749.
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  • [47]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950094
    Limberg, C.; Göpfert, J. P.; Wersing, H.; Ritter, H. (2020): Prototype-Based Online Learning on Homogeneously Labeled Streaming Data. In: Igor Farkaš; Paolo Masulli; Stefan Wermter (Hrsg.): Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II. Cham: Springer International Publishing. (Lecture Notes in Computer Science, 12397). S. 204-213.
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  • [46]
    2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982085
    Göpfert, J. P.; Wersing, H.; Hammer, B. (2019): Recovering Localized Adversarial Attacks. In: Igor V. Tetko; Věra Kůrková; Pavel Karpov; Fabian Theis (Hrsg.): Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation. 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part I. Cham: Springer International Publishing. (Lecture Notes in Computer Science, ). S. 302-311.
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  • [45]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982084
    Losing, V.; Yoshikawa, T.; Hasenjaeger, M.; Hammer, B.; Wersing, H. (2019): Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units. In: 2019 International Conference on Robotics and Automation (ICRA). IEEE. S. 9530-9536.
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  • [44]
    2019 | Preprint | Veröffentlicht | PUB-ID: 2934181
    Göpfert, J. P.; Wersing, H.; Hammer, B. (2019): Adversarial attacks hidden in plain sight
    PUB | DOI | arXiv
     
  • [43]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982088
    Losing, V.; Wersing, H.; Hammer, B. (2018): Enhancing Very Fast Decision Trees with Local Split-Time Predictions. In: 2018 IEEE International Conference on Data Mining (ICDM). IEEE. S. 287-296.
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  • [42]
    2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914730 OA
    Losing, V.; Hammer, B.; Wersing, H. (2018): Incremental on-line learning: A review and comparison of state of the art algorithms Neurocomputing,275: 1261-1274.
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  • [41]
    2017 | Konferenzbeitrag | PUB-ID: 2914734 OA
    Losing, V.; Hammer, B.; Wersing, H. (2017): Self-Adjusting Memory: How to Deal with Diverse Drift Types. International Joint Conferences on Artificial Intelligence.
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  • [40]
    2017 | Konferenzbeitrag | PUB-ID: 2914732 OA
    Losing, V.; Hammer, B.; Wersing, H. (2017): Personalized Maneuver Prediction at Intersections.
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  • [39]
    2016 | Konferenzbeitrag | PUB-ID: 2907624 OA
    Losing, V.; Hammer, B.; Wersing, H. (2016): Choosing the Best Algorithm for an Incremental On-line Learning Task.
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  • [38]
    2016 | Konferenzbeitrag | PUB-ID: 2908455 OA
    Losing, V.; Hammer, B.; Wersing, H. (2016): Dedicated Memory Models for Continual Learning in the Presence of Concept Drift.
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  • [37]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2907622 OA
    Losing, V.; Hammer, B.; Wersing, H. (2016): KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift. In: 2016 IEEE 16th International Conference on Data Mining (ICDM). Piscataway, NJ: IEEE. S. 291-300.
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  • [36]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772413
    Fischer, L.; Hammer, B.; Wersing, H. (2015): Efficient rejection strategies for prototype-based classification Neurocomputing,169:(SI): 334-342.
    PUB | DOI | WoS
     
  • [35]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2776021 OA
    Losing, V.; Hammer, B.; Wersing, H. (2015): Interactive Online Learning for Obstacle Classification on a Mobile Robot. IEEE.
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  • [34]
    2014 | Patent | PUB-ID: 2906899
    Wersing, H.; Queißer, J. (01.06.2016): System for Controlling an Automated Device
    PUB | Download (ext.)
     
  • [33]
    2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673548
    Fischer, L.; Hammer, B.; Wersing, H. (2014): Rejection strategies for learning vector quantization. In: Michel Verleysen (Hrsg.): ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium: i6doc.com. S. 41-46.
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  • [32]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2425561
    Dornbusch, D.; Haschke, R.; Menzel, S.; Wersing, H. (2012): Decomposition of Multimodal Data for Affordance-based Identification of Potential Grasps. SciTePress. S. 585-589.
    PUB | DOI
     
  • [31]
    2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2604349
    Lang, C.; Wachsmuth, S.; Hanheide, M.; Wersing, H. (2012): Facial Communicative Signals - Valence Recognition in Task-Oriented Human-Robot Interaction International Journal of Social Robotics - Special Issue on Measuring Human-Robot Interaction,4:(3): 249-262.
    PUB | DOI | WoS
     
  • [30]
    2012 | Report | PUB-ID: 2467027 OA
    Lang, C.; Wachsmuth, S.; Hanheide, M.; Wersing, H. (2012): Facial Communicative Signal Interpretation in Human-Robot Interaction by Discriminative Video Subsequence Selection.
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  • [29]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2376395
    John, S.; Wersing, H.; Ritter, H. (2010): An iterative approach to local-PCA. In: Neural Networks (IJCNN), The 2010 International Joint Conference on. S. 1-6.
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  • [28]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2034704
    Lang, C.; Wachsmuth, S.; Wersing, H.; Hanheide, M. (2010): Facial Expressions as Feedback Cue in Human-Robot Interaction - a Comparison between Human and Automatic Recognition Performances. In: IEEE Computer Society; Institute of Electrical and Electronics Engineers (Hrsg.): Workshop on CVPR for Human Communicative Behavior Analysis. San Francisco, California, USA: IEEE. S. 79-85.
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  • [27]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2034035
    Denecke, A.; Ayllon Clemente, I.; Wersing, H.; Eggert, J.; Steil, J. J. (2010): Figure-ground segmentation using metrics adaptation in levelset methods. In: European Symposium on Artificial Neural Networks. S. 417-422.
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  • [26]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2019022
    Dornbusch, D.; Haschke, R.; Menzel, S.; Wersing, H. (2010): Correlating shape and functional properties using decomposition approaches. In: Proc. FLAIRS-23. AAAI. S. 398-403.
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  • [25]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2019017
    Dornbusch, D.; Haschke, R.; Menzel, S.; Wersing, H. (2010): Finding Correlations in Multimodal Data Using Decomposition Approaches. In: Proc. ESANN 2010. Belgium: d-facto. S. 253-258.
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  • [24]
    2009 | Patent | PUB-ID: 2637645
    Wersing, H.; Götting, M.; Steil, J. J. (2009): Adaptive scene dependent filters in online learning environments
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  • [23]
    2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969815
    Denecke, A.; Wersing, H.; Steil, J. J.; Körner, E. (2009): Online figure-ground segmentation with adaptive metrics in Generalized LVQ Neurocomputing,72:(7-9): 1470-1482.
    PUB | DOI | WoS
     
  • [22]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1969825
    Denecke, A.; Wersing, H.; Steil, J. J.; Körner, E. (2009): Incremental Figure-Ground Segmentation using localized adaptive metrics in LVQ. In: International Workshop on Self-Organizing Maps (WSOM). S. 45-53.
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  • [21]
    2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969830
    Kirstein, S.; Denecke, A.; Hasler, S.; Wersing, H.; Gross, H. - M.; Körner, E. (2009): A Vision Architecture for Unconstrained and Incremental Learning of Multiple Categories Memetic Computing,1:(4): 291-304.
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  • [20]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1991920
    Lang, C.; Hanheide, M.; Lohse, M.; Wersing, H.; Sagerer, G. (2009): Feedback Interpretation based on Facial Expressions in Human–Robot Interaction. In: International Symposium on Robot and Human Interactive Communication (RO-MAN'09). Toyama, Japan: IEEE. S. 189-194.
    PUB | DOI
     
  • [19]
    2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142096
    Denecke, A.; Wersing, H.; Steil, J. J.; Körner, E. (2008): Robust object segmentation by adaptive metrics in Generalized LVQ. In: Proc. of the European Symposium on Artificial Neural Networks (ESANN). S. 319-324.
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  • [18]
    2007 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1996923 OA
    Wersing, H.; Kirstein, S.; Götting, M.; Brandl, H.; Dunn, M.; Mikhailova, I.; Görick, C.; Steil, J. J.; Ritter, H.; Körner, E. (2007): Online Learning of Objects and Faces in an Integrated Biologically Motivated Architecture. In: Proceedings of the 5th International Conference on Computer Vision Systems (ICVS 2007) . Bielefeld: Bielefeld University.
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  • [17]
    2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1632803
    Wersing, H.; Kirstein, S.; Götting, M.; Brandl, H.; Dunn, M.; Mikhailova, I.; Görick, C.; Steil, J. J.; Ritter, H.; Körner, E. (2007): Online Learning of Objects in a Biologically Motivated Visual Architecture International Journal of Neural Systems,17:(04): 219-230.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [16]
    2007 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1594761 OA
    Steil, J. J.; Götting, M.; Wersing, H.; Körner, E.; Ritter, H. (2007): Adaptive scene dependent filters for segmentation and online learning of visual objects Neurocomputing,70:(7-9): 1235-1246.
    PUB | PDF | DOI | WoS
     
  • [15]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142151 OA
    Götting, M.; Steil, J. J.; Wersing, H.; Körner, E.; Ritter, H. (2006): Adaptive scene-dependent filters in online learning environments. In: New issues in neurocomputing. 13th European Symposium on Artificial Neural Networks 2005. S. 101-106.
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  • [14]
    2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2142182
    Weng, S.; Wersing, H.; Steil, J. J.; Ritter, H. (2006): Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions IEEE Trans. Neural Networks,17:(4): 843-862.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [13]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142157
    Steil, J. J.; Wersing, H. (2006): Recent Trends in Online Learning for Cognitive Robotics. In: M. Verleysen (Hrsg.): Proc. European Symposium on Artifical Neural Networks. d-side publications.
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  • [12]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142171
    Wersing, H.; Kirstein, S.; Götting, M.; Brandl, H.; Dunn, M.; Mikhailova, I.; Görick, C.; Steil, J. J.; Ritter, H.; Körner, E. (2006): A biologically motivated system for unconstrained online learning of visual objects. In: Stefanos Kollias (Hrsg.): Proc. of the Int. Conf. on Artificial Neural Networks (ICANN). Berlin, Heidelberg: Springer Berlin Heidelberg. (2). S. 508-517.
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  • [11]
    2004 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2714352
    Ontrup, J.; Wersing, H.; Ritter, H. (2004): A Computational Feature Binding Model of Human Texture Perception Cognitive Processing,5:(1): 32-44.
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  • [10]
    2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1613503
    Nattkemper, T. W.; Wersing, H.; Schubert, W.; Ritter, H. (2002): A neural network architecture for automatic segmentation of fluorescence micrographs. In: Neurocomputing. ELSEVIER SCIENCE BV. (NEUROCOMPUTING, 48). S. 357-367.
    PUB | DOI | WoS
     
  • [9]
    2001 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1616820
    Wersing, H.; Beyn, W. - J.; Ritter, H. (2001): Dynamical stability conditions for recurrent neural networks with unsaturating piecewise linear transfer functions Neural Computation,13:(8): 1811-1825.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [8]
    2001 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2142293
    Wersing, H.; Steil, J. J.; Ritter, H. (2001): A Competitive Layer Model for Feature Binding and Sensory Segmentation Neural Computation,13:(2): 357-387.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [7]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2375211
    Nattkemper, T. W.; Wersing, H.; Schubert, W.; Ritter, H. (2000): A Neural Network Architecture for Automatic Segmentation of Fluorescence Micrographs. In: Michel Verleysen (Hrsg.): Proc. of the 8th Europ. Symp. on Art. Neur. Netw. (ESANN).
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  • [6]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2374799
    Nattkemper, T. W.; Wersing, H.; Schubert, W.; Ritter, H. (2000): Fluorescence Micrograph Segmentation by Gestalt-Based Feature Binding. In: Proc. of the Int. Joint Conf. on Neur. Netw. (IJCNN). Como, Italy. (1). S. 248-254.
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  • [5]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2714744
    Nattkemper, T. W.; Wersing, H.; Schubert, W.; Ritter, H. (2000): Automatic Evaluation of Multi-Parameter Fluorescence Micrographs with a Neural Network Architecture. In: Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, METMBS '00. Las Vegas, USA. (2). S. 739-744.
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  • [4]
    2000 | Dissertation | PUB-ID: 2434189
    Wersing, H. (2000): Spatial feature binding and learning in competitive neural layer architectures. Göttingen: Cuvillier.
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  • [3]
    1999 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2714834
    Wersing, H.; Ritter, H. (1999): Backtracking Deterministic Annealing for Constraint Satisfaction Problems. In: ICANN 99, Ninth Int. Conf. Artifical Neural Netwworks. London: IEE. (Conference Publication / IEE, 470). S. 868-875.
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  • [2]
    1999 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2714852
    Wersing, H.; Ritter, H. (1999): Feature Binding and Relaxation Labeling with the Competitive Layer Model. In: Proceedings. ESANN '99, 7th European Symposium on Artificial Neural Networks. Bruges. S. 295-300.
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  • [1]
    1997 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142325
    Wersing, H.; Steil, J. J.; Ritter, H. (1997): A Layered Recurrent Neural Network for Feature Grouping. In: Wulfram Gerstner; Alain Germond; Martin Hasler; Jean-Daniel Nicoud (Hrsg.): Int. Conf. on Artificial Neural Networks. S. 439-444.
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