Skip to main content Skip to main navigation

Publications

Displaying results 351 to 360 of 682.

  1. Nabeel Khalid; Mohsin Munir; Christoffer Edlund; Timothy R Jackson; Johan Tryggy; Rickard Sjögren; Andreas Dengel; Sheraz Ahmed

    DeepCIS: An end-to-end Pipeline for Cell-type aware Instance Segmentation in Microscopic Images

    In: IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI’21) JOINTLY ORGANISED WITH THE 17TH IEEE-EMBS INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN’21). IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI-2021), July 27-30, Athens, Europe, Greece, ISBN 978-1-6654-4770-6, IEEE, 8/2021.

  2. Nabeel Khalid; Mohsin Munir; Christoffer Edlund; Timothy R Jackson; Johan Tryggy; Rickard Sjögren; Andreas Dengel; Sheraz Ahmed

    DeepCeNS: An end-to-end Pipeline for Cell and Nucleus Segmentation in Microscopic Images

    In: 2021 International Joint Conference on Neural Networks (IJCNN). International Joint Conference on Neural Networks (IJCNN-2021), July 18-20, Glasgow, United Kingdom, IJCNN, 2021.

  3. Christoffer Edlund; Timothy R. Jackson; Nabeel Khalid; Nicola Bevan; Timothy Dale; Andreas Dengel; Sheraz Ahmed; Johan Trygg; Rickard Sjögren

    LIVECell—A large-scale dataset for label-free live cell segmentation

    In: Nature Research, Vol. None, Pages 1-8, Nature Methods, 8/2021.

  4. Michael Lutter; Kim Listmann; Jan Peters

    Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

    In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), November 3-8, Macau, China, Pages 7718-7725, IEEE, 2019.

  5. Michael Lutter; Christian Ritter; Jan Peters

    Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

    In: 7th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2019), May 6-9, New Orleans, LA, USA, OpenReview.net, 2019.

  6. Vignesh Prasad; Dorothea Koert; Ruth Stock-Homburg; Jan Peters; Georgia Chalvatzaki

    MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction

    In: 21st IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2022), November 28-30, Ginowan, Japan, Pages 472-479, IEEE, 2022.

  7. Riad Akrour; Davide Tateo; Jan Peters

    Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 44, No. 10, Pages 6795-6806, IEEE, 2022.

  8. Fabio Muratore; Fabio Ramos; Greg Turk; Wenhao Yu; Michael Gienger; Jan Peters

    Robot Learning From Randomized Simulations: A Review

    In: Frontiers in Robotics and AI, Vol. 9, Pages 0-10, Frontiers, 2022.

  9. Simone Parisi; Davide Tateo; Maximilian Hensel; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning

    In: Algorithms, Vol. 15, No. 3, Pages 0-10, MDPI, 2022.

  10. Jihao Andreas Lin; Joe Watson; Pascal Klink; Jan Peters

    Function-Space Regularization for Deep Bayesian Classification

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2307.06055, Pages 0-10, arXiv, 2023.

Year

More options