16 citations · 30 across the 9 of their papers we have counts for
10 papers
Constraint-Guided Enterprise Data Mapping with Large Language Models
Sebastian Monka, Pramod Anantharam, Thien Vo Minh +1
Enterprise entity alignment must handle semi-structured records, implicit attributes, and unit or granularity mismatches. Manual matching is still common in practice, but does not…
Seeing and Knowing in the Wild: Open-domain Visual Entity Recognition with Large-scale Knowledge Graphs via Contrastive Learning
Hongkuan Zhou, Lavdim Halilaj, Sebastian Monka +5
Open-domain visual entity recognition aims to identify and link entities depicted in images to a vast and evolving set of real-world concepts, such as those found in Wikidata. Unli…
Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
Sebastian Monka, Irlan Grangel-González, Stefan Schmid +4
Knowledge graphs (KGs) have transformed data management within the manufacturing industry, offering effective means for integrating disparate data sources through shared and struct…
Robust Visual Representation Learning with Multi-modal Prior Knowledge for Image Classification Under Distribution Shift
Hongkuan Zhou, Lavdim Halilaj, Sebastian Monka +4
Despite the remarkable success of deep neural networks (DNNs) in computer vision, they fail to remain high-performing when facing distribution shifts between training and testing d…
nuScenes Knowledge Graph -- A comprehensive semantic representation of traffic scenes for trajectory prediction
Leon Mlodzian, Zhigang Sun, Hendrik Berkemeyer +5
Trajectory prediction in traffic scenes involves accurately forecasting the behaviour of surrounding vehicles. To achieve this objective it is crucial to consider contextual inform…
Context-driven Visual Object Recognition based on Knowledge Graphs
Sebastian Monka, Lavdim Halilaj, Achim Rettinger
Current deep learning methods for object recognition are purely data-driven and require a large number of training samples to achieve good results. Due to their sole dependence on…
A Survey on Knowledge Graph-based Methods for Automated Driving
Juergen Luettin, Sebastian Monka, Cory Henson +1
Automated driving is one of the most active research areas in computer science. Deep learning methods have made remarkable breakthroughs in machine learning in general and in autom…
A Survey on Visual Transfer Learning using Knowledge Graphs
Sebastian Monka, Lavdim Halilaj, Achim Rettinger
Recent approaches of computer vision utilize deep learning methods as they perform quite well if training and testing domains follow the same underlying data distribution. However,…
Learning Visual Models using a Knowledge Graph as a Trainer
Sebastian Monka, Lavdim Halilaj, Stefan Schmid +1
Traditional computer vision approaches, based on neural networks (NN), are typically trained on a large amount of image data. By minimizing the cross-entropy loss between a predict…
Real-time on-board obstacle avoidance for UAVs based on embedded stereo vision
Boitumelo Ruf, Sebastian Monka, Matthias Kollmann +1
In order to improve usability and safety, modern unmanned aerial vehicles (UAVs) are equipped with sensors to monitor the environment, such as laser-scanners and cameras. One impor…