Zobrazeno 1 - 10
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pro vyhledávání: '"Mecke, A."'
In this paper we assess how well users know biometric authentication methods, how they perceive them, and if they have misconceptions about them. We present the results of an online survey that we conducted in two rounds (2019, N=57; and 2023, N=47)
Externí odkaz:
http://arxiv.org/abs/2410.12661
Many important decisions in our everyday lives, such as authentication via biometric models, are made by Artificial Intelligence (AI) systems. These can be in poor alignment with human expectations, and testing them on clear-cut existing data may not
Externí odkaz:
http://arxiv.org/abs/2409.12801
Chiral active fluids show the emergence of a turbulent behavior characterized by multiple dynamic vortices whose maximum size is specific for each experimental system. This is in contrast to hydrodynamic simulations in which the size of vortices is o
Externí odkaz:
http://arxiv.org/abs/2408.12820
Publikováno v:
Communications Physics, Vol 7, Iss 1, Pp 1-10 (2024)
Abstract Chiral active fluids show the emergence of a turbulent behaviour characterised by multiple dynamic vortices whose maximum size varies for each experimental system, depending on conditions not yet identified. We propose and develop an approac
Externí odkaz:
https://doaj.org/article/0429c7c7a4ed4be48e3760f67f75e504
Deep generative models have the potential to fundamentally change the way we create high-fidelity digital content but are often hard to control. Prompting a generative model is a promising recent development that in principle enables end-users to cre
Externí odkaz:
http://arxiv.org/abs/2209.01390
We investigate how multiple sliders with and without feedforward visualizations influence users' control of generative models. In an online study (N=138), we collected a dataset of people interacting with a generative adversarial network (StyleGAN2)
Externí odkaz:
http://arxiv.org/abs/2202.00965
Gaussian random fields are among the most important models of amorphous spatial structures and appear across length scales in a variety of physical, biological, and geological applications, from composite materials to geospatial data. Anisotropy in s
Externí odkaz:
http://arxiv.org/abs/2111.13349
Autor:
Klatt, Michael Andreas, Mecke, Klaus
Publikováno v:
EPL 128, 60001 (2019)
Astronomy, biophysics, and material science often depend on the possibility to extract information out of faint spatial signals. Here we present a morphometric analysis technique to quantify the shape of structural deviations in greyscale images. It
Externí odkaz:
http://arxiv.org/abs/2111.13348
Publikováno v:
National Science Open, Vol 3 (2024)
Externí odkaz:
https://doaj.org/article/74088b3fde534adab9fe8814a6171fb4
Publikováno v:
A&A 653, A16 (2021)
We develop an automatic bubble-recognition routine based on Minkowski functionals (MF) and tensors (MT) to detect bubble-like interstellar structures in optical emission line images. Minkowski functionals and MT are powerful mathematical tools for pa
Externí odkaz:
http://arxiv.org/abs/2108.11641