Towards assisted input and output data analysis in manufacturing simulation: the EDASim approach. - Tjorben Bogon; Ingo J. Timm; Ulrich Jessen; Markus Schmitz; Sigrid Wenzel; Andreas D. Lattner; Dimitris C. Paraskevopoulos; Sven Spieckermann (WSC, 2012)

Die Digitale Agenda der BA - Wie sich ein öffentlicher Dienstleister der Digitalisierung stellt. - Markus Schmitz (Digitalisierung im Spannungsfeld von Politik, Wirtschaft, Wissenschaft und Recht (1), 2018)

Enabling of Predictive Maintenance in the Brownfield through Low-Cost Sensors, an IIoT-Architecture and Machine Learning. - Patrick Straus; Markus Schmitz; René Wöstmann; Jochen Deuse (IEEE BigData, 2018)

Enabling Rewards for Reinforcement Learning in Laser Beam Welding processes through Deep Learning. - Markus Schmitz; Florian Pinsker; Alexander Ruhri; Beibei Jiang; Georgij Safronov (ICMLA, 2020)

Auf dem Weg zu einer ethisch verantwortungsvollen Datennutzung. - Markus Schmitz (Inform. Spektrum, 2020)

Towards Real-World Force-Sensitive Robotic Assembly through Deep Reinforcement Learning in Simulations. - Marius Hebecker; Jens Lambrecht; Markus Schmitz (AIM, 2021)

Verifying the Applicability of Synthetic Image Generation for Object Detection in Industrial Quality Inspection. - Majid Shirazi; Markus Schmitz; Simon Janssen; Anabelle Thies; Georgij Safronov; Amr Rizk; Peter Mayr 006; Philipp Engelhardt (ICMLA, 2021)

Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation. - Jibinraj Antony; Florian Schlather; Georgij Safronov; Markus Schmitz; Kristof Van Laerhoven (CoRR, 2021)

An Application-centric Perspective on Industrial Artificial Intelligence. - Markus Schmitz; Dilara Yesilbas (AMCIS, 2022)

Robotic Analysation Methodology for Multidirectional Additive Manufacturing Process Configuration. - Markus Schmitz; Florian Menz; Mathias Hüsing; Burkhard Corves (ARK, 2022)

Deep Reinforcement Learning for Robotic Control in High-Dexterity Assembly Tasks - A Reward Curriculum Approach. - Lars Leyendecker; Markus Schmitz; Hans Aoyang Zhou; Vladimir Samsonov; Marius Rittstieg; Daniel Lütticke (Int. J. Semantic Comput., 2022)

Machine Learning in Industrial Applications: Insights Gained from Selected Studies. - Markus Schmitz (2022)

Suitability test of virtual reality applications for older people considering the spatial orientation ability. - Dan Bürger; Stefan Pastel; Chien-Hsi Chen; Katharina Petri; Markus Schmitz; Leon Wischerath; Kerstin Witte (Virtual Real., 2023)

Monitoring and control of Additive Manufacturing with the Robot Operating System. - M. Mierzwa; K. Mäde; Rahul Sharma; Uwe Reisgen; J. Wiartalla; Markus Schmitz; Mathias Hüsing; Burkhard Corves (ICCAD, 2024)

ROS2WASM: Bringing the Robot Operating System to the Web. - Tobias Fischer 001; Isabel Paredes; Michael Batchelor; Thorsten Beier; Jesse Haviland; Silvio Traversaro; Wolf Vollprecht; Markus Schmitz; Michael Milford (CoRR, 2024)