14 citations · 22 across the 6 of their papers we have counts for
6 papers
Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey
Julian Wörmann, Daniel Bogdoll, Christian Brunner +49
The availability of representative datasets is an essential prerequisite for many successful artificial intelligence and machine learning models. However, in real life applications…
Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spaces
Alexander Sagel, Julian Wörmann, Hao Shen
Distance-based dynamic texture recognition is an important research field in multimedia processing with applications ranging from retrieval to segmentation of video data. Based on…
Knowledge as Invariance -- History and Perspectives of Knowledge-augmented Machine Learning
Alexander Sagel, Amit Sahu, Stefan Matthes +5
Research in machine learning is at a turning point. While supervised deep learning has conquered the field at a breathtaking pace and demonstrated the ability to solve inference pr…
Dynamic Variational Autoencoders for Visual Process Modeling
Alexander Sagel, Hao Shen
This work studies the problem of modeling visual processes by leveraging deep generative architectures for learning linear, Gaussian representations from observed sequences. We pro…
Alignment Distances on Systems of Bags
Alexander Sagel, Martin Kleinsteuber
Recent research in image and video recognition indicates that many visual processes can be thought of as being generated by a time-varying generative model. A nearby descriptive mo…
Texture Retrieval via the Scattering Transform
Alexander Sagel, Dominik Meyer, Hao Shen
This work studies the problem of content-based image retrieval, specifically, texture retrieval. It focuses on feature extraction and similarity measure for texture images. Our app…