1 citations · 1 across the 7 of their papers we have counts for
7 papers
Why Ranking Anomaly Detection Algorithms Isn't as Reliable as You May Think
Simon Klüttermann, Jérôme Rutinowski, Frederik Polachowski +1
Anomaly detection is a safety-critical machine learning problem with applications ranging from fraud detection to network intrusion prevention and industrial monitoring. Despite th…
Enhancing Long-Term Re-Identification Robustness Using Synthetic Data: A Comparative Analysis
Christian Pionzewski, Rebecca Rademacher, Jérôme Rutinowski +5
This contribution explores the impact of synthetic training data usage and the prediction of material wear and aging in the context of re-identification. Different experimental set…
Extremely asymmetric diffraction as a method of determining magneto-optical constants for X-rays near absorption edges
M A Andreeva, Yu. Repchenko, A G Smekhova +3
The spectral dependence of the Bragg peak position under conditions of extremely asymmetric diffraction has been analyzed in the kinematical and dynamical approximations of the dif…
On the Effectiveness of Heterogeneous Ensemble Methods for Re-identification
Simon Klüttermann, Jérôme Rutinowski, Anh Nguyen +3
In this contribution, we introduce a novel ensemble method for the re-identification of industrial entities, using images of chipwood pallets and galvanized metal plates as dataset…
Object Pose Estimation Annotation Pipeline for Multi-view Monocular Camera Systems in Industrial Settings
Hazem Youssef, Frederik Polachowski, Jérôme Rutinowski +2
Object localization, and more specifically object pose estimation, in large industrial spaces such as warehouses and production facilities, is essential for material flow operation…
Semi-Automated Computer Vision based Tracking of Multiple Industrial Entities -- A Framework and Dataset Creation Approach
Jérôme Rutinowski, Hazem Youssef, Sven Franke +4
This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, ba…
On the Applicability of Synthetic Data for Re-Identification
Jérôme Rutinowski, Bhargav Vankayalapati, Nils Schwenzfeier +2
This contribution demonstrates the feasibility of applying Generative Adversarial Networks (GANs) on images of EPAL pallet blocks for dataset enhancement in the context of re-ident…