Conferences and Journals

  1. Karayil, T., Irfan, A., Raue, F., Hees, J., & Dengel, A. (2019). A Reinforcement Learning Approach for Sequential Spatial Transformer Networks. In ICANN. International Conference on Artificial Neural Networks (ICANN), Germany. Springer. Accepted for publication.
  2. Azimi, F., Raue, F., Hees, J., & Dengel, A. (2019). A Reinforcement Learning Approach for Sequential Spatial Transformer Networks. In ICANN. International Conference on Artificial Neural Networks (ICANN), Germany. Springer. Accepted for publication.
  3. Moser, B., Raue, F., Hees, J., & Dengel, A. (2019). Comparison between U-Net and U-ReNet models in OCR tasks. In Proceedings of the 28th International Conference on Artificial Neural Networks. International Conference on Artificial Neural Networks (ICANN-2019), September 17-19, Munich, Germany. Springer. Accepted for publication.
  4. Blandfort, P., Karayil, T., Raue, F., Hees, J., & Dengel, A. (2019). Fusion Strategies for Learning User Embeddings with Neural Networks. In 2019 International Joint Conference on Neural Networks. International Joint Conference on Neural Networks (IJCNN-2019), July 14-19, Budapest, Hungary. IEEE.
  5. Palacio, S., Folz, J., Hees, J., Raue, F., & Dengel, A. (2018). What do Deep Networks Like to See. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Website
  6. Mozaffari Chanijani, S. S., Raue, F., Agne, S., Bukhari, S. S., & Dengel, A. (2018). Reading Type Classification based on Generative Models and Bidirectional Long Short-Term Memory. In User Interfaces for Spatial-Temporal Data Analysis Workshops (UISTDA), Proceedings of the 23rd International Conference on Intelligent User Interfaces. ACM. Website
  7. Raue, F., Dengel, A., Breuel, T. M., & Liwicki, M. (2018). Symbol Grounding Association in Multimodal Sequences with Missing Elements. In Journal of Artificial Intelligence Research (JAIR) – Special Track on Deep Learning, Knowledge Representation, and Reasoning. Website
  8. Raue, F., Palacio, S., Dengel, A., & Liwicki, M. (2017). Classless Association using Neural Networks. In International Conference on Artificial Neural Networks (ICANN) 2017. Website
  9. Raue, F., Liwicki, M., & Dengel, A. (2016). Symbolic Association Learning inspired by the Symbol Grounding Problem. In Workshop New Challenges in Neural Computation (NC^2). Website
  10. Raue, F., Palacio, S., Breuel, T. M., Byeon, W., Dengel, A., & Liwicki, M. (2016). Multimodal Symbolic Association using Parallel Multilayer Perceptron. In International Conference on Artificial Neural Networks (ICANN) 2016. Website
  11. Raue, F., Byeon, W., Breuel, T. M., & Liwicki, M. (2015). Symbol Grounding in Multimodal Sequences using Recurrent Neural Networks. In Workshop Cognitive Computation: Integrating Neural and Symbolic Approaches at NIPS 2015. Website
  12. Raue, F., Byeon, W., Breuel, T. M., & Liwicki, M. (2015). Parallel Sequence Classification using Recurrent Neural Networks and Alignment. In Document Analysis and Recognition (ICDAR), 2015 13th International Conference on (pp. 581–585). IEEE.
  13. Byeon, W., Breuel, T. M., Raue, F., & Liwicki, M. (2015). Scene Labeling with LSTM Recurrent Neural Networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 3547–3555).

Talks

  1. Raue, F., Palacio, S., Dengel, A., & Liwicki, M. (2016). Unsupervised Association using Multilayer Perceptron. Online, Poster presented at Deep Learning Summer School, 1st-8th August, Montreal-Canada. Website
  2. Raue, F., Palacio, S., Breuel, T., Byeon, W., Dengel, A., & Liwicki, M. (2015). Multimodal Symbolic Association using Parallel Multilayer Perceptron. Online, Poster presented at Multimodal Machine Learning Workshop (MMML), 11th December, Montreal-Canada. Website
  3. Byeon, W., Breuel, T., Raue, F., & Liwicki, M. (2015). Scene Labeling with LSTM Recurrent Neural Networks. Online, Poster presented at SUNw: Scene Understanding Workshop, 12th June, Boston-USA. Website