24 citations · 33 across the 12 of their papers we have counts for
20 papers
Kernel Affine Hull Machines as Compute-Efficient Encoders for Frozen Semantic Spaces
Mohit Kumar, Somayeh Kargaran, Bernhard A. Moser +1
Transformer-based semantic encoders are effective for retrieval, but in many deployments the recurring bottleneck is online query encoding rather than offline corpus indexing. This…
Operator-Theoretic Framework for Gradient-Free Federated Learning
Mohit Kumar, Mathias Brucker, Alexander Valentinitsch +4
Federated learning must address heterogeneity, strict communication and computation limits, and privacy while ensuring performance. We propose an operator-theoretic framework that…
Automatic Bounding Box Annotation with Small Training Data Sets for Industrial Manufacturing
Manuela Geiß, Raphael Wagner, Martin Baresch +2
In the past few years, object detection has attracted a lot of attention in the context of human-robot collaboration and Industry 5.0 due to enormous quality improvements in deep l…
Fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing
Manuela Geiß, Martin Baresch, Georgios Chasparis +3
We present an end-to-end framework for fast retraining of object detection models in human-robot-collaboration. Our Faster R-CNN based setup covers the whole workflow of automatic…
Arc-Completion of 2-Colored Best Match Graphs to Binary-Explainable Best Match Graphs
David Schaller, Manuela Geiß, Marc Hellmuth +1
Best match graphs (BMGs) are vertex-colored digraphs that naturally arise in mathematical phylogenetics to formalize the notion of evolutionary closest genes w.r.t. an a priori unk…
Heuristic Algorithms for Best Match Graph Editing
David Schaller, Manuela Geiß, Marc Hellmuth +1
Best match graphs (BMGs) are a class of colored digraphs that naturally appear in mathematical phylogenetics and can be approximated with the help of similarity measures between ge…