Zobrazeno 1 - 10
of 4 461
pro vyhledávání: '"P. Andreadis"'
Autor:
Ioannis I. Andreadis, Christos I. Gioumouxouzis, Georgios K. Eleftheriadis, Dimitrios G. Fatouros
Publikováno v:
Pharmaceutics, Vol 14, Iss 12, p 2782 (2022)
In the original publication [...]
Externí odkaz:
https://doaj.org/article/1bd961e6730c42a5afedb11d56a1f54e
Autor:
Kapoor, Anand Utsav, Baes, Maarten, van der Wel, Arjen, Gebek, Andrea, Camps, Peter, Smith, Aaron, Boquien, Médéric, Andreadis, Nick, Vicens, Sebastien
Current galaxy formation simulations often approximate star-formation, necessitating models of star-forming regions to produce observables. In the first paper of the series, we introduced TODDLERS, a time-resolved model of UV-mm emission from star-fo
Externí odkaz:
http://arxiv.org/abs/2410.01067
Deep neural models have achieved state of the art performance on a wide range of problems in computer science, especially in computer vision. However, deep neural networks often require large datasets of labeled samples to generalize effectively, and
Externí odkaz:
http://arxiv.org/abs/2408.07221
For many real-world optimization problems it is possible to perform partial evaluations, meaning that the impact of changing a few variables on a solution's fitness can be computed very efficiently. It has been shown that such partial evaluations can
Externí odkaz:
http://arxiv.org/abs/2402.10757
Autor:
Andreadis, Georgios, Mulder, Joas I., Bouter, Anton, Bosman, Peter A. N., Alderliesten, Tanja
The transformation model is an essential component of any deformable image registration approach. It provides a representation of physical deformations between images, thereby defining the range and realism of registrations that can be found. Two typ
Externí odkaz:
http://arxiv.org/abs/2401.16867
Autor:
Baes, Maarten, Mosenkov, Aleksandr, Kelly, Raymond, Abdurro'uf, Andreadis, Nick, Tulu, Sena Bokona, Camps, Peter, Emana, Abdissa Tassama, Fritz, Jacopo, Gebek, Andrea, Kovacic, Inja, La Marca, Antonio, Martorano, Marco, Nersesian, Angelos, Rodriguez-Gomez, Vicente, Tortora, Crescenzo, Trcka, Ana, Meulen, Bert Vander, van der Wel, Arjen, Wang, Lingyu
Galaxy sizes correlate with many other important properties of galaxies, and the cosmic evolution of galaxy sizes is an important observational diagnostic for constraining galaxy evolution models. The effective radius is probably the most widely used
Externí odkaz:
http://arxiv.org/abs/2401.04225
Autor:
Baes, Maarten, Gebek, Andrea, Trcka, Ana, Camps, Peter, van der Wel, Arjen, Abdurro'uf, Andreadis, Nick, Tulu, Sena Bokona, Emana, Abdissa Tassama, Fritz, Jacopo, Kelly, Raymond, Kovacic, Inja, La Marca, Antonio, Martorano, Marco, Mosenkov, Aleksandr, Nersesian, Angelos, Rodriguez-Gomez, Vicente, Tortora, Crescenzo, Meulen, Bert Vander, Wang, Lingyu
Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer post-processing th
Externí odkaz:
http://arxiv.org/abs/2401.04224
Autor:
Passali, Tatiana, Chatzikyriakidis, Efstathios, Andreadis, Stelios, Stavropoulos, Thanos G., Matonaki, Anastasia, Fachantidis, Anestis, Tsoumakas, Grigorios
Long sentences have been a persistent issue in written communication for many years since they make it challenging for readers to grasp the main points or follow the initial intention of the writer. This survey, conducted using the PRISMA guidelines,
Externí odkaz:
http://arxiv.org/abs/2312.05172
Autor:
Juan José León, Nía Oetiker, Nicolás Torres, Nicolás Bruna, Evgenii Oskolkov, Pedro Lei, Andrey N. Kuzmin, Kaiwen Chen, Stelios Andreadis, Blaine A. Pfeifer, Mark T. Swihart, Paras N. Prasad, José Pérez-Donoso
Publikováno v:
Microbial Cell Factories, Vol 23, Iss 1, Pp 1-12 (2024)
Abstract Background Rare-earth sulfide nanoparticles (NPs) could harness the optical and magnetic features of rare-earth ions for applications in nanotechnology. However, reports of their synthesis are scarce and typically require high temperatures a
Externí odkaz:
https://doaj.org/article/fb63ec1fb7fb4f338f691ecd78ab441a
Semantic segmentation for spherical data is a challenging problem in machine learning since conventional planar approaches require projecting the spherical image to the Euclidean plane. Representing the signal on a fundamentally different topology in
Externí odkaz:
http://arxiv.org/abs/2307.02658