Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Iris Huijben"'
Autor:
Ruud JG van van Sloun, Merel M van Gilst, Sebastiaan Overeem, Allessandro C Rossi, Lieke WA Hermans, Iris Huijben
We used a dataset of nocturnal PSG recordings, collected as part of the Healthbed study, which main aim was development of technologies for sleep analyses. The dataset includes one clinical video-PSG recording for each subject, made according to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::478670900752e90d4d43bd3cf5407e06
https://doi.org/10.36227/techrxiv.16722403.v1
https://doi.org/10.36227/techrxiv.16722403.v1
Publikováno v:
Proceedings of the 9th International Conference on Learning Representations, ICLR 2021
Pure TUe
Pure TUe
Neural data compression has been shown to outperform classical methods in terms of $RD$ performance, with results still improving rapidly. At a high level, neural compression is based on an autoencoder that tries to reconstruct the input instance fro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c2fd200690734d161d73358759bea2a
https://research.tue.nl/nl/publications/b2b9422d-76d1-4cf1-bfe0-c13cc116756c
https://research.tue.nl/nl/publications/b2b9422d-76d1-4cf1-bfe0-c13cc116756c
Publikováno v:
Pure TUe
8th International Conference on Learning Representations, ICLR 2020
8th International Conference on Learning Representations, ICLR 2020
The field of deep learning is commonly concerned with optimizing predictive models using large pre-acquired datasets of densely sampled datapoints or signals. In this work, we demonstrate that the deep learning paradigm can be extended to incorporate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6eded8d091a414aeb9baecc5467caa33
https://research.tue.nl/en/publications/69ddddef-ed02-4293-830a-2cb4e1ec35b3
https://research.tue.nl/en/publications/69ddddef-ed02-4293-830a-2cb4e1ec35b3