212 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Technische Universität DarmstadtDE16 papers
- Darmstadt University of Applied SciencesDE4 papers
- Fraunhofer-GesellschaftDE4 papers
- Norwegian University of Science and TechnologyNO3 papers
- Saarland UniversityDE3 papers
- University of LjubljanaSI3 papers
- Changchun Institute of Optics, Fine Mechanics and PhysicsCN2 papers
- Fraunhofer Institute for Secure Information TechnologyDE2 papers
- INESC TECPT2 papers
- Max Planck Institute for InformaticsDE2 papers
- Universidad Autónoma de MadridES2 papers
- University of Arkansas at Little RockUS2 papers
6 papers · 1 filter
Background Subtraction with Real-time Semantic Segmentation
Dongdong Zeng, Xiang Chen, Ming Zhu +2
Accurate and fast foreground object extraction is very important for object tracking and recognition in video surveillance. Although many background subtraction (BGS) methods have…
Conceptual Analysis of Resource Meta-information
Christian Neuss, Robert E. Kent
It's ease of use and the availability of browsers for various platforms have paved the way for the enormous popularity that the World Wide Web currently enjoys. In the near future,…
Creating a Web Analysis and Visualization Environment
Robert E. Kent, Christian Neuss
Due to the rapid growth of the World Wide Web, resource discovery becomes an increasing problem. As an answer to the demand for information management, a third generation of World-…
Combining Background Subtraction Algorithms with Convolutional Neural Network
Dongdong Zeng, Ming Zhu, Arjan Kuijper
Accurate and fast extraction of foreground object is a key prerequisite for a wide range of computer vision applications such as object tracking and recognition. Thus, enormous bac…
How Bad is Good enough: Noisy annotations for instrument pose estimation
David Kügler, Anirban Mukhopadhyay
Though analysis of Medical Images by Deep Learning achieves unprecedented results across various applications, the effect of \emph{noisy training annotations} is rarely studied in…
Exploring Adversarial Examples: Patterns of One-Pixel Attacks
David Kügler, Alexander Distergoft, Arjan Kuijper +1
Failure cases of black-box deep learning, e.g. adversarial examples, might have severe consequences in healthcare. Yet such failures are mostly studied in the context of real-world…