Markus Schmitz

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 11

Top Topics

Fault Detection

Cognitive Scientists

Reinforcement Learning

Minimally Invasive Surgery

Top Venues

Inform. Spektrum

Publications

M. Mierzwa, K. Mäde, R. Sharma, Uwe Reisgen, J. Wiartalla, Markus Schmitz, Mathias Hüsing, Burkhard Corves
Monitoring and control of Additive Manufacturing with the Robot Operating System. ICCAD (2024)
Markus Schmitz, Florian Menz, Mathias Hüsing, Burkhard Corves
Robotic Analysation Methodology for Multidirectional Additive Manufacturing Process Configuration. ARK (2022)
Lars Leyendecker, Markus Schmitz, Hans Aoyang Zhou, Vladimir Samsonov, Marius Rittstieg, Daniel Lütticke
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach. Int. J. Semantic Comput. 16 (3) (2022)
Markus Schmitz, Dilara Yesilbas
An Application-centric Perspective on Industrial Artificial Intelligence. AMCIS (2022)
Marius Hebecker, Jens Lambrecht, Markus Schmitz
Towards Real-World Force-Sensitive Robotic Assembly through Deep Reinforcement Learning in Simulations. AIM (2021)
Jibinraj Antony, Florian Schlather, Georgij Safronov, Markus Schmitz, Kristof Van Laerhoven
Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation. CoRR (2021)
Majid Shirazi, Markus Schmitz, Simon Janssen, Anabelle Thies, Georgij Safronov, Amr Rizk, Peter Mayr, Philipp Engelhardt
Verifying the Applicability of Synthetic Image Generation for Object Detection in Industrial Quality Inspection. ICMLA (2021)
Lars Leyendecker, Markus Schmitz, Hans Aoyang Zhou, Vladimir Samsonov, Marius Rittstieg, Daniel Lütticke
Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach. IRC (2021)
Markus Schmitz, Florian Pinsker, Alexander Ruhri, Beibei Jiang, Georgij Safronov
Enabling Rewards for Reinforcement Learning in Laser Beam Welding processes through Deep Learning. ICMLA (2020)
Markus Schmitz
Auf dem Weg zu einer ethisch verantwortungsvollen Datennutzung. Inform. Spektrum 43 (6) (2020)
Patrick Straus, Markus Schmitz, René Wöstmann, Jochen Deuse
Enabling of Predictive Maintenance in the Brownfield through Low-Cost Sensors, an IIoT-Architecture and Machine Learning. IEEE BigData (2018)
Tjorben Bogon, Ingo J. Timm, Ulrich Jessen, Markus Schmitz, Sigrid Wenzel, Andreas D. Lattner, Dimitris C. Paraskevopoulos, Sven Spieckermann
Towards assisted input and output data analysis in manufacturing simulation: the EDASim approach. WSC (2012)