Skip to main content Skip to main navigation

Publications

Displaying results 341 to 350 of 579.

  1. Matthias Rosynski; Frank Kirchner; Matias Valdenegro-Toro

    Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

    In: ICBINB@NeurIPS 2020 - Bridging the gap between theory and empiricism in probabilistic machine learning. I Can't Believe It's Not Better! Workshop (ICBINB-2020), located at NeurIPS 2020, December 12, Virtual, arXiv, 2020.

  2. Lauren Michelle Pfeifer; Matias Valdenegro-Toro

    Automatic Detection and Classification of Tick-borne Skin Lesions using Deep Learning

    In: Workshop: LXAI Research @ NeurIPS 2020. LatinX in AI Research Workshop (LXAI-2020), located at NeurIPS2020, December 7, Virtual, Keine, 2020.

  3. Peter Hevesi; Ramprasad Chinnaswamy Devaraj; Matthias Tschöpe; Oliver Petter; Janis Nikolaus Elfert; Vitor Fortes Rey; Marco Hirsch; Paul Lukowicz

    Towards Construction Progress Estimation Based on Images Captured on Site

    In: EAI IndustrialIoT 2020 - 4th EAI International Conference on Industrial IoT Technologies and Applications. EAI International Conference on Industrial IoT Technologies and Applications (EAI IndustrialIoT-2020), December 11, Online-Conference, Springer, 2020.

  4. Kumar Shridhar; Joonho Lee; Hideaki Hayashi; Purvanshi Mehta; Brian Kenji Iwana; Seokjun Kang; Seiichi Uchida; Sheraz Ahmed; Andreas Dengel

    ProbAct: A Probabilistic Activation Functionfor Deep Neural Networks

    In: OPT2020: 12th Annual Workshop on Optimization for Machine Learning. Workshop on Optimization for Machine Learning (OPT-2020), located at NeurIPS2020, December 11-12, Vancouver, Canada, ArXiv, 2019.

  5. Abhash Sinha; Martin Jenckel; Syed Saqib Bukhari; Andreas Dengel

    Unsupervised OCR Model Evaluation Using GAN

    In: Proceedings ICDAR'19. International Conference on Document Analysis and Recognition (ICDAR-2019), September 20-25, Sydney, Australia, Pages 1256-1261, ISBN 978-1-7281-3015-6, IEEE, 9/2019.

  6. Redy Andriyansah; Syed Saqib Bukhari; Martin Jenckel; Andreas Dengel

    Using Balanced Training to Minimize Biased Classification

    In: HIP '19: Proceedings of the 5th International Workshop on Historical Document Imaging and Processing. International Workshop on Historical Document Imaging and Processing (HIP), Sydney, Australia, Pages 31-36, ISBN 978-1-4503-7668-6, Association for Computing Machinery, 9/2019.

  7. Jigyasa Singh Katrolia; Lars Krämer; Jason Raphael Rambach; Bruno Mirbach; Didier Stricker

    An Adversarial Training based Framework for Depth Domain Adaptation

    In: Proceedings of the 16th VISAPP. International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP-2021), 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, February 8-10, online, Springer, 2021.

  8. Mohammad Mohsin Reza; Syed Saqib Bukhari; Martin Jenckel; Andreas Dengel

    Table Localization and Segmentation using GAN and CNN

    In: 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW). International Conference on Document Analysis and Recognition Workshops (ICDARW-2019), September 22-25, Sydney, Australia, Pages 152-157, Vol. 5, ISBN 978-1-7281-5055-0, Association for Computing Machinery, 9/2019.

  9. Andreas Dengel

    Some Shades of Grey!: Interpretability and Explainability of Deep Neural Networks

    In: Proceedings WCRML19. ACM Workshop on Crossmodal Learning and Application, Ottawa, Canada, ISBN 978-1-4503-6780-6, Association for Computing Machinery, New York, 6/2019.

  10. Marco Schreyer; Timur Sattarov; Damian Borth; Andreas Dengel; Bernd Reimer

    Künstliche Intelligenz in der Wirtschaftsprüfung - Identifikation ungewöhnlicher Buchungen in der Finanzbuchhaltung

    In: Die Wirtschaftsprüfung (WPg), Vol. 71, Pages 674-681, IDW Verlag, 6/2018.

Year

More options