50 Publikationen

Alle markieren

  • [50]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959418
    Göpfert, J. P., Kuhl, U., Hindemith, L., Wersing, H., and Hammer, B. (2021). Intuitiveness in Active Teaching. IEEE Transactions on Human-Machine Systems, 1-10.
    PUB | DOI | WoS
     
  • [49]
    2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2950092
    Limberg, C., Wersing, H., and Ritter, H. (2020). Beyond Cross-Validation—Accuracy Estimation for Incremental and Active Learning Models. Machine Learning and Knowledge Extraction 2, 327-346.
    PUB | DOI | WoS
     
  • [48]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950093
    Limberg, C., Wersing, H., and Ritter, H. (2020). “Accuracy Estimation for an Incrementally Learning Cooperative Inventory Assistant Robot” in Neural Information Processing. 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part II, Yang, H., Pasupa, K., Leung, A. C. - S., Kwok, J. T., Chan, J. H., and King, I. eds. Lecture Notes in Computer Science, vol. 12533, (Cham: Springer International Publishing), 738-749.
    PUB | DOI
     
  • [47]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950094
    Limberg, C., Göpfert, J. P., Wersing, H., and Ritter, H. (2020). “Prototype-Based Online Learning on Homogeneously Labeled Streaming Data” in Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II, Farkaš, I., Masulli, P., and Wermter, S. eds. Lecture Notes in Computer Science, vol. 12397, (Cham: Springer International Publishing), 204-213.
    PUB | DOI
     
  • [46]
    2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982085
    Göpfert, J. P., Wersing, H., and Hammer, B. (2019). “Recovering Localized Adversarial Attacks” in 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, Tetko, I. V., Kůrková, V., Karpov, P., and Theis, F. eds. Lecture Notes in Computer Science (Cham: Springer International Publishing), 302-311.
    PUB | DOI
     
  • [45]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982084
    Losing, V., Yoshikawa, T., Hasenjaeger, M., Hammer, B., and 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), 9530-9536.
    PUB | DOI
     
  • [44]
    2019 | Preprint | Veröffentlicht | PUB-ID: 2934181
    Göpfert, J. P., Wersing, H., and Hammer, B. (2019). Adversarial attacks hidden in plain sight.
    PUB | DOI | arXiv
     
  • [43]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982088
    Losing, V., Wersing, H., and Hammer, B. (2018). “Enhancing Very Fast Decision Trees with Local Split-Time Predictions” in 2018 IEEE International Conference on Data Mining (ICDM) (IEEE), 287-296.
    PUB | DOI
     
  • [42]
    2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914730 OA
    Losing, V., Hammer, B., and Wersing, H. (2018). Incremental on-line learning: A review and comparison of state of the art algorithms. Neurocomputing 275, 1261-1274.
    PUB | PDF | DOI | WoS
     
  • [41]
    2017 | Konferenzbeitrag | PUB-ID: 2914734 OA
    Losing, V., Hammer, B., and Wersing, H. (2017).“Self-Adjusting Memory: How to Deal with Diverse Drift Types”. Presented at the International Joint Conference on Artificial Intelligence (IJCAI) 2017, Melbourne.
    PUB | PDF | DOI
     
  • [40]
    2017 | Konferenzbeitrag | PUB-ID: 2914732 OA
    Losing, V., Hammer, B., and Wersing, H. (2017).“Personalized Maneuver Prediction at Intersections”. Presented at the IEEE Intelligent Transportation Systems Conference 2017, Yokohama.
    PUB | PDF
     
  • [39]
    2016 | Konferenzbeitrag | PUB-ID: 2907624 OA
    Losing, V., Hammer, B., and Wersing, H. (2016).“Choosing the Best Algorithm for an Incremental On-line Learning Task”. Presented at the European Symposium on Artificial Neural Networks, Brügge.
    PUB | PDF
     
  • [38]
    2016 | Konferenzbeitrag | PUB-ID: 2908455 OA
    Losing, V., Hammer, B., and Wersing, H. (2016).“Dedicated Memory Models for Continual Learning in the Presence of Concept Drift”. Presented at the Continual Learning Workshop of the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS), Barcelona.
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  • [37]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2907622 OA
    Losing, V., Hammer, B., and 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), 291-300.
    PUB | PDF | DOI
     
  • [36]
    2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2772413
    Fischer, L., Hammer, B., and Wersing, H. (2015). Efficient rejection strategies for prototype-based classification. Neurocomputing 169, 334-342.
    PUB | DOI | WoS
     
  • [35]
    2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2776021 OA
    Losing, V., Hammer, B., and Wersing, H. (2015).“Interactive Online Learning for Obstacle Classification on a Mobile Robot”. Presented at the International Joint Conference on Neural Networks, Killarney, Ireland.
    PUB | PDF | DOI
     
  • [34]
    2014 | Patent | PUB-ID: 2906899
    Wersing, H., and 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., and Wersing, H. (2014). “Rejection strategies for learning vector quantization” in ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Verleysen, M. ed. (Bruges, Belgium: i6doc.com), 41-46.
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  • [32]
    2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2425561
    Dornbusch, D., Haschke, R., Menzel, S., and Wersing, H. (2012).“Decomposition of Multimodal Data for Affordance-based Identification of Potential Grasps”. Presented at the International Conference on Pattern Recognition Applications and Methods, Vilamoura, Algarve, Portugal.
    PUB | DOI
     
  • [31]
    2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2604349
    Lang, C., Wachsmuth, S., Hanheide, M., and 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, 249-262.
    PUB | DOI | WoS
     
  • [30]
    2012 | Report | PUB-ID: 2467027 OA
    Lang, C., Wachsmuth, S., Hanheide, M., and Wersing, H. (2012). Facial Communicative Signal Interpretation in Human-Robot Interaction by Discriminative Video Subsequence Selection.
    PUB | PDF
     
  • [29]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2376395
    John, S., Wersing, H., and Ritter, H. (2010). “An iterative approach to local-PCA” in Neural Networks (IJCNN), The 2010 International Joint Conference on 1-6.
    PUB | DOI
     
  • [28]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2034704
    Lang, C., Wachsmuth, S., Wersing, H., and Hanheide, M. (2010). “Facial Expressions as Feedback Cue in Human-Robot Interaction - a Comparison between Human and Automatic Recognition Performances” in Workshop on CVPR for Human Communicative Behavior Analysis, IEEE Computer Society, and Institute of Electrical and Electronics Engineers eds. (San Francisco, California, USA: IEEE), 79-85.
    PUB | DOI
     
  • [27]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2034035
    Denecke, A., Ayllon Clemente, I., Wersing, H., Eggert, J., and Steil, J. J. (2010). “Figure-ground segmentation using metrics adaptation in levelset methods” in European Symposium on Artificial Neural Networks 417-422.
    PUB
     
  • [26]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2019022
    Dornbusch, D., Haschke, R., Menzel, S., and Wersing, H. (2010). “Correlating shape and functional properties using decomposition approaches” in Proc. FLAIRS-23 (AAAI), 398-403.
    PUB
     
  • [25]
    2010 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2019017
    Dornbusch, D., Haschke, R., Menzel, S., and Wersing, H. (2010). “Finding Correlations in Multimodal Data Using Decomposition Approaches” in Proc. ESANN 2010 (Belgium: d-facto), 253-258.
    PUB
     
  • [24]
    2009 | Patent | PUB-ID: 2637645
    Wersing, H., Götting, M., and Steil, J. J. (2009). Adaptive scene dependent filters in online learning environments.
    PUB
     
  • [23]
    2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969815
    Denecke, A., Wersing, H., Steil, J. J., and Körner, E. (2009). Online figure-ground segmentation with adaptive metrics in Generalized LVQ. Neurocomputing 72, 1470-1482.
    PUB | DOI | WoS
     
  • [22]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1969825
    Denecke, A., Wersing, H., Steil, J. J., and Körner, E. (2009). “Incremental Figure-Ground Segmentation using localized adaptive metrics in LVQ” in International Workshop on Self-Organizing Maps (WSOM) 45-53.
    PUB | DOI
     
  • [21]
    2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1969830
    Kirstein, S., Denecke, A., Hasler, S., Wersing, H., Gross, H. - M., and Körner, E. (2009). A Vision Architecture for Unconstrained and Incremental Learning of Multiple Categories. Memetic Computing 1, 291-304.
    PUB | DOI
     
  • [20]
    2009 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1991920
    Lang, C., Hanheide, M., Lohse, M., Wersing, H., and 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), 189-194.
    PUB | DOI
     
  • [19]
    2008 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142096
    Denecke, A., Wersing, H., Steil, J. J., and Körner, E. (2008). “Robust object segmentation by adaptive metrics in Generalized LVQ” in Proc. of the European Symposium on Artificial Neural Networks (ESANN) 319-324.
    PUB
     
  • [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., and 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).
    PUB | PDF | DOI
     
  • [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., and Körner, E. (2007). Online Learning of Objects in a Biologically Motivated Visual Architecture. International Journal of Neural Systems 17, 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., and Ritter, H. (2007). Adaptive scene dependent filters for segmentation and online learning of visual objects. Neurocomputing 70, 1235-1246.
    PUB | PDF | DOI | WoS
     
  • [15]
    2006 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2142182
    Weng, S., Wersing, H., Steil, J. J., and Ritter, H. (2006). Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions. IEEE Trans. Neural Networks 17, 843-862.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [14]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142151 OA
    Götting, M., Steil, J. J., Wersing, H., Körner, E., and Ritter, H. (2006). “Adaptive scene-dependent filters in online learning environments” in New issues in neurocomputing. 13th European Symposium on Artificial Neural Networks 2005 101-106.
    PUB | PDF
     
  • [13]
    2006 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142157
    Steil, J. J., and Wersing, H. (2006). “Recent Trends in Online Learning for Cognitive Robotics” in Proc. European Symposium on Artifical Neural Networks, Verleysen, M. ed. (d-side publications).
    PUB
     
  • [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., and Körner, E. (2006). “A biologically motivated system for unconstrained online learning of visual objects” in Proc. of the Int. Conf. on Artificial Neural Networks (ICANN), Kollias, S. ed., vol. 2, (Berlin, Heidelberg: Springer Berlin Heidelberg), 508-517.
    PUB | DOI
     
  • [11]
    2004 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2714352
    Ontrup, J., Wersing, H., and Ritter, H. (2004). A Computational Feature Binding Model of Human Texture Perception. Cognitive Processing 5, 32-44.
    PUB
     
  • [10]
    2002 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 1613503
    Nattkemper, T. W., Wersing, H., Schubert, W., and Ritter, H. (2002). “A neural network architecture for automatic segmentation of fluorescence micrographs” in Neurocomputing NEUROCOMPUTING, vol. 48, (ELSEVIER SCIENCE BV), 357-367.
    PUB | DOI | WoS
     
  • [9]
    2001 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1616820
    Wersing, H., Beyn, W. - J., and Ritter, H. (2001). Dynamical stability conditions for recurrent neural networks with unsaturating piecewise linear transfer functions. Neural Computation 13, 1811-1825.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [8]
    2001 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2142293
    Wersing, H., Steil, J. J., and Ritter, H. (2001). A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation 13, 357-387.
    PUB | DOI | WoS | PubMed | Europe PMC
     
  • [7]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2375211
    Nattkemper, T. W., Wersing, H., Schubert, W., and Ritter, H. (2000). “A Neural Network Architecture for Automatic Segmentation of Fluorescence Micrographs” in Proc. of the 8th Europ. Symp. on Art. Neur. Netw. (ESANN), Verleysen, M. ed.
    PUB
     
  • [6]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2374799
    Nattkemper, T. W., Wersing, H., Schubert, W., and Ritter, H. (2000). “Fluorescence Micrograph Segmentation by Gestalt-Based Feature Binding” in Proc. of the Int. Joint Conf. on Neur. Netw. (IJCNN), vol. 1, (Como, Italy), 248-254.
    PUB
     
  • [5]
    2000 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2714744
    Nattkemper, T. W., Wersing, H., Schubert, W., and 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, vol. 2, (Las Vegas, USA), 739-744.
    PUB
     
  • [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., and Ritter, H. (1999). “Backtracking Deterministic Annealing for Constraint Satisfaction Problems” in ICANN 99, Ninth Int. Conf. Artifical Neural Netwworks Conference Publication / IEE, vol. 470, (London: IEE), 868-875.
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  • [2]
    1999 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2714852
    Wersing, H., and 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), 295-300.
    PUB
     
  • [1]
    1997 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2142325
    Wersing, H., Steil, J. J., and Ritter, H. (1997). “A Layered Recurrent Neural Network for Feature Grouping” in Int. Conf. on Artificial Neural Networks, Gerstner, W., Germond, A., Hasler, M., and Nicoud, J. - D. eds. 439-444.
    PUB
     

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