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of 6
pro vyhledávání: '"Rolff, Tim"'
Autor:
Kelm, André, Hannemann, Niels, Heberle, Bruno, Schmidt, Lucas, Rolff, Tim, Wilms, Christian, Yaghoubi, Ehsan, Frintrop, Simone
This study introduces a novel expert generation method that dynamically reduces task and computational complexity without compromising predictive performance. It is based on a new hierarchical classification network topology that combines sequential
Externí odkaz:
http://arxiv.org/abs/2403.05601
Autor:
Kelm, André Peter, Hannemann, Niels, Heberle, Bruno, Schmidt, Lucas, Rolff, Tim, Wilms, Christian, Yaghoubi, Ehsan, Frintrop, Simone
This paper introduces a novel network topology that seamlessly integrates dynamic inference cost with a top-down attention mechanism, addressing two significant gaps in traditional deep learning models. Drawing inspiration from human perception, we c
Externí odkaz:
http://arxiv.org/abs/2308.05128
Large industrial facilities such as particle accelerators and nuclear power plants are critical infrastructures for scientific research and industrial processes. These facilities are complex systems that not only require regular maintenance and upgra
Externí odkaz:
http://arxiv.org/abs/2307.09860
Autor:
Li, Ke, Rolff, Tim, Schmidt, Susanne, Bacher, Reinhard, Frintrop, Simone, Leemans, Wim, Steinicke, Frank
Neural radiance field (NeRF), in particular its extension by instant neural graphics primitives, is a novel rendering method for view synthesis that uses real-world images to build photo-realistic immersive virtual scenes. Despite its potential, rese
Externí odkaz:
http://arxiv.org/abs/2211.13494
Publikováno v:
Frontiers in Virtual Reality; 2024, p1-16, 16p
We address the automatic segmentation of computer tomographic scans of ancient clay tablets with cuneiform inscriptions enclosed inside a clay envelope. Such separation of parts of similar material properties in the scan enables domain scientists to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae28a49a73c7b3289fb9c87a668a8f88