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including - 1 LARGE sample with low-resolution data (micro-CT, VERSA510) - splitted in I, II, III, IV, V - 3 SUB-Samples MEDIUM-resolution (cutted down from above LARGE sample, scanned with micro-CT, ZEISS VERSA510) - 3 SUB-Samples HIGH-resolution (same as MEDIUM, scanned with nano-CT, ZEISS ULTRA810)
Glass Particles (soda-lime glass), particle size distribution 5 to 50 µm
Reuse of articles in the Dissertation with permission from Elsevier (via RightsLink, 2017).
Supplementary image dataset of the ISPRS International Journal of Geoinformation publication "Fully Automated Pose Estimation of Historical Images in the Context of 4D Geographic Information Systems Utilizing Machine Learning Methods". Historical image benchmark dataset including feature matches and four scene reconstructions. The dataset can be used for testing and evaluating feature matching methods on exclusively historical images. Additionally, the dataset can easily be extended as all tie point information is provided.
A workflow is introduced to automatically measure water stages based on image measurements using deep learning. So far, most camera gauges do not provide the needed robustness to achieve accurate water stage measurements because of changing environmental conditions. The novel, suggested approach is based on two CNNs (i.e. FCN and SegNet) to identify water in imagery. The image information is transformed into metric water level values intersecting the extracted water contour with a 3D model. The workflow allows for the densification of river monitoring networks based on low-cost camera gauges in various scenarios.
In this paper, we tested whether impulsive decision-making (1) differs between individuals with substance use disorders (SUD) or non-substance-related addictive disorders (ND) and healthy controls and (2) predicts the course of SUD and ND severity after one year.
Supplementary material to the publication: "Fast fourier transform and multi-Gaussian fitting of XRR data to determine the thickness of ALD grown thin films within the initial growth regime"
Medienbeilage zu ARRAY2019 Magazin der International Computer Music Association ICMA
Die Orchestrierung modularer Anlagen behandelt das verknüpfen von verschiedenen modularen Prozesseinheiten (PEA) sowohl aus verfahrenstechnischer als auch aus automatisierungstechnischer Sicht. Dabei sind eine Vielzahl von Aspekten zu berücksichtigen.