Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Tristan van Leeuwen"'
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-7 (2024)
Abstract This paper introduces ForametCeTera, a pioneering dataset designed to address the challenges associated with automating the analysis of benthic foraminifera in sediment cores. Foraminifera are sensitive sentinels of environmental change and
Externí odkaz:
https://doaj.org/article/23b0c0ee50b34512a70a759f7aaa03d2
Autor:
Francien G. Bossema, Willem Jan Palenstijn, Arlen Heginbotham, Madeline Corona, Tristan van Leeuwen, Robert van Liere, Jan Dorscheid, Daniel O’Flynn, Joanne Dyer, Erma Hermens, K. Joost Batenburg
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Visualizing the internal structure of museum objects is a crucial step in acquiring knowledge about the origin, state, and composition of cultural heritage artifacts. Among the most powerful techniques for exposing the interior of museum obj
Externí odkaz:
https://doaj.org/article/fee87716d60643b3b6934145b53a422b
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-12 (2023)
Abstract Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However, s
Externí odkaz:
https://doaj.org/article/08816b2001274bf29e9911c736045761
Autor:
Maximilian B. Kiss, Francien G. Bossema, Paul J. C. van Laar, Suzan Meijer, Felix Lucka, Tristan van Leeuwen, K. Joost Batenburg
Publikováno v:
Heritage Science, Vol 11, Iss 1, Pp 1-14 (2023)
Abstract Computed tomography (CT) is a powerful non-invasive tool to analyze cultural heritage objects by allowing museum professionals to obtain 3D information about the objects’ interior. These insights can help with the conservation or restorati
Externí odkaz:
https://doaj.org/article/e76cb7e2a176496bbcd948651b195301
Autor:
Hamid Fathi, Tristan van Leeuwen
Publikováno v:
Mathematics, Vol 12, Iss 10, p 1524 (2024)
X-ray tomography is an effective non-destructive testing method for industrial quality control. Limited-angle tomography can be used to reduce the amount of data that need to be acquired and thereby speed up the process. In some industrial applicatio
Externí odkaz:
https://doaj.org/article/978f394c6f1940e7a41372b7de85a70f
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Although X-ray imaging is used routinely in industry for high-throughput product quality control, its capability to detect internal defects has strong limitations. The main challenge stems from the superposition of multiple object features w
Externí odkaz:
https://doaj.org/article/5b253503b8524b00abed939ee99aea26
Autor:
Andreas Tataris, Tristan van Leeuwen
Publikováno v:
Mathematics, Vol 10, Iss 2, p 216 (2022)
We study the inverse scattering problem for a Schrödinger operator related to a static wave operator with variable velocity, using the GLM (Gelfand–Levitan–Marchenko) integral equation. We assume to have noisy scattering data, and we derive a st
Externí odkaz:
https://doaj.org/article/9f24fd2a38ca4b62bd002875340d5d49
Publikováno v:
Journal of Imaging, Vol 7, Iss 7, p 104 (2021)
X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone frag
Externí odkaz:
https://doaj.org/article/8055f03819404d1da705f113a8b319bf
Autor:
Mathé T. Zeegers, Daniël M. Pelt, Tristan van Leeuwen, Robert van Liere, Kees Joost Batenburg
Publikováno v:
Journal of Imaging, Vol 6, Iss 12, p 132 (2020)
An important challenge in hyperspectral imaging tasks is to cope with the large number of spectral bins. Common spectral data reduction methods do not take prior knowledge about the task into account. Consequently, sparsely occurring features that ma
Externí odkaz:
https://doaj.org/article/1018fe423f94464dafb9bc0059fba8f1
Publikováno v:
International Journal of Geophysics, Vol 2011 (2011)
We explore the use of stochastic optimization methods for seismic waveform inversion. The basic principle of such methods is to randomly draw a batch of realizations of a given misfit function and goes back to the 1950s. The ultimate goal of such an
Externí odkaz:
https://doaj.org/article/0f149546c2dc415e914b141e916d8c7a