9 papers
SIL: Symbiotic Interactive Learning for Language-Conditioned Human-Agent Co-Adaptation
Linus Nwankwo, Bjoern Ellensohn, Christian Rauch +1
Today's autonomous agents, largely driven by foundation models (FMs), can understand natural language instructions and solve long-horizon tasks with human-like reasoning. However,…
SteelDS: A High-Resolution Video Dataset of E40 Steel Scrap for Object Detection and Instance Segmentation
Melanie Neubauer, Christian Rauch, Gerald Koinig +3
This dataset provides high-resolution, annotated video sequences of shredded E40-grade steel and copper scrap on a conveyor belt. Captured in a controlled laboratory environment, t…
PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation
Melanie Neubauer, Elmar Rueckert, Christian Rauch
Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recycling and weeding. Existing…
Rock Classification through Knowledge-Enhanced Deep Learning: A Hybrid Mineral-Based Approach
Iye Szin Ang, Martin Johannes Findl, Elisabeth Hauzinger +5
Automated rock classification from mineral composition presents a significant challenge in geological applications, with critical implications for material recycling, resource mana…
ReLI: A Language-Agnostic Approach to Human-Robot Interaction
Linus Nwankwo, Bjoern Ellensohn, Ozan Ãzdenizci +1
Adapting autonomous agents for real-world industrial, domestic, and other daily tasks is currently gaining momentum. However, in global or cross-lingual application contexts, ensur…
Privacy-Aware Lifelong Learning
Ozan Ãzdenizci, Elmar Rueckert, Robert Legenstein
Lifelong learning algorithms enable models to incrementally acquire new knowledge without forgetting previously learned information. Contrarily, the field of machine unlearning foc…