Paul Scheikl



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Types of publications

Journal article
Book chapter / Article in edited volumes
Authored book
Translation
Thesis
Edited Volume
Conference contribution
Other publication type
Unpublished / Preprint

Publication year

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Abstract

Journal

Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud (2024) Henrich P, Gyenes B, Scheikl P, Neumann G, Mathis-Ullrich F Conference contribution Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects (2024) Scheikl P, Schreiber N, Haas C, Freymuth N, Neumann G, Lioutikov R, Mathis-Ullrich F Journal article A surgical activity model of laparoscopic cholecystectomy for co-operation with collaborative robots (2024) Younis R, Yamlahi A, Bodenstedt S, Scheikl P, Kisilenko A, Daum M, Schulze A, et al. Journal article Sim-to-Real Transfer for Visual Reinforcement Learning of Deformable Object Manipulation for Robot-Assisted Surgery (2023) Scheikl PM, Tagliabue E, Gyenes B, Wagner M, Dall'Alba D, Fiorini P, Mathis-Ullrich F Journal article A learning robot for cognitive camera control in minimally invasive surgery (2021) Wagner M, Bihlmaier A, Kenngott HG, Mietkowski P, Scheikl PM, Bodenstedt S, Schiepe-Tiska A, et al. Journal article epiTracker: A Framework for Highly Reliable Particle Tracking for the Quantitative Analysis of Fish Movements in Tanks (2021) Bruch R, Scheikl PM, Mikut R, Loosli F, Reischl M Journal article Flexible Facile Tactile Sensor for Smart Vessel Phantoms (2021) Fischer N, Scheikl PM, Marzi C, Galindo-Blanco B, Kisilenko A, Müller-Stich BP, Wagner M, Mathis-Ullrich F Journal article Robots in the operating room—(co)operation during surgery Robotik im Operationssaal – (Ko‑)Operieren mit Kollege Roboter (2021) Mathis-Ullrich F, Scheikl PM Journal article, Review article Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning (2021) Scheikl PM, Gyenes B, Davitashvili T, Younis R, Schulze A, Mueller-Stich BP, Neumann G, et al. Conference contribution Deep learning for semantic segmentation of organs and tissues in laparoscopic surgery (2020) Scheikl PM, Laschewski S, Kisilenko A, Davitashvili T, Müller B, Capek M, Müller-Stich BP, et al. Journal article