Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Marcel Aach"'
Publikováno v:
Frontiers in High Performance Computing, Vol 2 (2024)
This manuscript presents the library AI4HPC with its architecture and components. The library enables large-scale trainings of AI models on High-Performance Computing systems. It addresses challenges in handling non-uniform datasets through data mani
Externí odkaz:
https://doaj.org/article/1de2ecdf8f244483a492e7adc9d72a3a
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-23 (2023)
Abstract Continuously increasing data volumes from multiple sources, such as simulation and experimental measurements, demand efficient algorithms for an analysis within a realistic timeframe. Deep learning models have proven to be capable of underst
Externí odkaz:
https://doaj.org/article/1ea7daa2801f435cb665bebd532759dc
Publikováno v:
Fluids, Vol 9, Iss 4, p 84 (2024)
This study presents a novel approach to using a gated recurrent unit (GRU) model, a deep neural network, to predict turbulent flows in a Lagrangian framework. The emerging velocity field is predicted based on experimental data from a strained turbule
Externí odkaz:
https://doaj.org/article/6eadbcce9cbd4b0a853fb639370a94b0
Autor:
Chadi Barakat, Marcel Aach, Andreas Schuppert, Sigurður Brynjólfsson, Sebastian Fritsch, Morris Riedel
Publikováno v:
Diagnostics, Vol 13, Iss 3, p 391 (2023)
The COVID-19 pandemic shed light on the need for quick diagnosis tools in healthcare, leading to the development of several algorithmic models for disease detection. Though these models are relatively easy to build, their training requires a lot of d
Externí odkaz:
https://doaj.org/article/4798b9c6e19c485cbd65769f87ab95a1
Autor:
Marcel Aach, Rocco Sedona, Andreas Lintermann, Gabriele Cavallaro, Helmut Neukirchen, Morris Riedel
Publikováno v:
IEEE 263-266 (2022). doi:10.1109/IGARSS46834.2022.9883257
2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 2022-07-17-2022-07-22
2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, 2022-07-17-2022-07-22
Deep Learning models have proven necessary in dealing with the challenges posed by the continuous growth of data volume acquired from satellites and the increasing complexity of new Remote Sensing applications. To obtain the best performance from suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68a60c094f12b5f587ce2e36ef03550a
https://hdl.handle.net/2128/32035
https://hdl.handle.net/2128/32035
Publikováno v:
2022 26th International Conference on Information Technology (IT)
IEEE 1-4 (2022). doi:10.1109/IT54280.2022.9743519
26th International Conference on Information Technology (IT), IT, Zabljak, Montenegro, 2022-02-16-2022-02-19
IEEE 1-4 (2022). doi:10.1109/IT54280.2022.9743519
26th International Conference on Information Technology (IT), IT, Zabljak, Montenegro, 2022-02-16-2022-02-19
Post-print (lokaútgáfa höfunda).
Sound localization is the ability of humans to determine the source direction of sounds that they hear. Emulating this capability in virtual environments can have various societally relevant applications enabl
Sound localization is the ability of humans to determine the source direction of sounds that they hear. Emulating this capability in virtual environments can have various societally relevant applications enabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc9cf7bed448bb8aa0b5a2337182162c