12 citations · 14 across the 4 of their papers we have counts for
5 papers
Relation-based Motion Prediction using Traffic Scene Graphs
Maximilian Zipfl, Felix Hertlein, Achim Rettinger +5
Representing relevant information of a traffic scene and understanding its environment is crucial for the success of autonomous driving. Modeling the surrounding of an autonomous c…
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…