PUB - Publikationen an der Universität Bielefeld

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• [12]
  

  2021 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2960159

  Moringen, A., Fleer, S., and Ritter, H. (2021). “Meta-learning Haptic Exploration of Simple 3D Objects” in 2021 IEEE World Haptics Conference (Piscataway, NJ: IEEE).

  PUB | PDF
   
• [11]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2949926

  Mohanty, S. P., Czakon, J., Kaczmarek, K. A., Pyskir, A., Tarasiewicz, P., Kunwar, S., Rohrbach, J., Luo, D., Prasad, M., Fleer, S., et al. (2020). Deep Learning for Understanding Satellite Imagery: An Experimental Survey. Frontiers in Artificial Intelligence 3:534696.

  PUB | PDF | DOI | WoS | PubMed | Europe PMC
   
• [10]
  

  2020 | Bielefelder E-Dissertation | PUB-ID: 2949123

  Fleer, S. (2020). Scaffolding for learning from reinforcement: Improving interaction learning. Bielefeld: Universität Bielefeld.

  PUB | Dateien verfügbar | DOI
   
• [9]
  

  2020 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2943876

  Moringen, A., Fleer, S., Walck, G., and Ritter, H. (2020). “Attention-based Robot Learning of Haptic Interaction” in Haptics: Science, Technology, Applications. 12th International Conference, EuroHaptics 2020, Leiden, The Netherlands, September 6–9, 2020, Proceedings, Nisky, I., Hartcher-O’Brien, J., Wiertlewski, M., and Smeets, J. eds. Lecture Notes in Computer Science, vol. 12272, (Cham: Springer), 462-470.

  PUB | PDF | DOI | Download (ext.)
   
• [8]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939850

  Fleer, S., Moringen, A., Klatzky, R. L., and Ritter, H. (2020). Learning efficient haptic shape exploration with a rigid tactile sensor array. PLOS ONE 15:e0226880.

  PUB | PDF | DOI | WoS | PubMed | Europe PMC | arXiv
   
• [7]
  

  2019 | Datenpublikation | PUB-ID: 2934182

  Fleer, S. (2019). Supplementary Material - Solving a tool-based interaction task using deep reinforcement learning with visual attention. Bielefeld University.

  PUB | Dateien verfügbar | DOI
   
• [6]
  

  2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2935994

  Fleer, S., and Ritter, H. (2019). “Solving a Tool-Based Interaction Task Using Deep Reinforcement Learning with Visual Attention” in Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization. WSOM 2019 Advances in Intelligent Systems and Computing , vol. 976, (Cham: Springer), 231-240.

  PUB | DOI | Download (ext.)
   
• [5]
  

  2019 | Datenpublikation | PUB-ID: 2936475

  Fleer, S., Moringen, A., Klatzky, R. L., and Ritter, H. (2019). Supplementary Material - Learning efficient haptic shape exploration with a rigid tactile sensor array. Bielefeld University.

  PUB | Dateien verfügbar | DOI
   
• [4]
  

  2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2939854

  Moringen, A., Fleer, S., and Ritter, H. (2019). “Scaffolding Haptic Attention with Controller Gating” 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, vol. 11727, (Cham: Springer), 669-684.

  PUB | DOI | Download (ext.)
   
• [3]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933709

  Fleer, S., and Ritter, H. (2019). “Skill Transfer for Mediated Interaction Learning” in 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) (Piscataway, NJ: IEEE).

  PUB | DOI | Download (ext.)
   
• [2]
  

  2019 | Konferenzbeitrag | PUB-ID: 2933988

  Melnik, A., Fleer, S., Schilling, M., and Ritter, H. (2019). “Modularization of End-to-End Learning: Case Study in Arcade Games” in 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Workshop on Causal Learning.

  PUB | arXiv
   
• [1]
  

  2017 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2914841

  Fleer, S., and Ritter, H. (2017). “Comparing Action Sets: Mutual Information as a Measure of Control” in Artificial Neural Networks and Machine Learning – ICANN 2017 Lecture Notes in Computer Science (Cham: Springer International Publishing), 68-75.

  PUB | DOI