A Spatio-Temporal-Semantic Environment Representation for Autonomous Mobile Robots equipped with various Sensor Systems. - Mark Niemeyer; Sebastian Pütz; Joachim Hertzberg (MFI, 2022)

Scalable Evaluation Pipeline of CNN-Based Perception for Robotic Sensor Data Under Different Environment Conditions. - Naeem Iqbal; Mark Niemeyer; Jan Christoph Krause; Joachim Hertzberg (ECMR, 2023)

Towards model-based automation of plant-specific weed regulation. - Marian Renz; Mark Niemeyer; Joachim Hertzberg (GIL Jahrestagung, 2023)

Object Anchoring for Autonomous Robots Using the Spatio-Temporal-Semantic Environment Representation SEEREP. - Mark Niemeyer; Marian Renz; Joachim Hertzberg (KI, 2023)

Cognitive Weeding: An Approach to Single-Plant Specific Weed Regulation. - Mark Niemeyer; Marian Renz; Maren Pukrop; David Hagemann; Tim Zurheide; Daniel Di Marco; Markus Höferlin; Philipp Stark; Florian Rahe; Matthias Igelbrink; Mario Jenz; Thomas Jarmer 001; et al. (Künstliche Intell., 2023)

Towards Auto-generated Ground Truth for Evaluation of Perception Systems in Agriculture. - Jan Christoph Krause; Mark Niemeyer; Janosch Bajorath; Naeem Iqbal; Joachim Hertzberg (ECCV Workshops (3), 2024)

Consolidation of Symbolic Instances Using Sensor Data via Tracklet Merging for Long-Term Monitoring of Crops. - Mark Niemeyer; Joachim Hertzberg; Grzegorz Cielniak (ECCV Workshops (3), 2024)

Streamlined Acquisition of Large Sensor Data for Autonomous Mobile Robots to Enable Efficient Creation and Analysis of Datasets. - Mark Niemeyer; Julian Arkenau; Sebastian Pütz; Joachim Hertzberg (ICRA, 2024)