Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Casper Hansen"'
Autor:
Espen Jimenez-Solem, Tonny S. Petersen, Casper Hansen, Christian Hansen, Christina Lioma, Christian Igel, Wouter Boomsma, Oswin Krause, Stephan Lorenzen, Raghavendra Selvan, Janne Petersen, Martin Erik Nyeland, Mikkel Zöllner Ankarfeldt, Gert Mehl Virenfeldt, Matilde Winther-Jensen, Allan Linneberg, Mostafa Mehdipour Ghazi, Nicki Detlefsen, Andreas David Lauritzen, Abraham George Smith, Marleen de Bruijne, Bulat Ibragimov, Jens Petersen, Martin Lillholm, Jon Middleton, Stine Hasling Mogensen, Hans-Christian Thorsen-Meyer, Anders Perner, Marie Helleberg, Benjamin Skov Kaas-Hansen, Mikkel Bonde, Alexander Bonde, Akshay Pai, Mads Nielsen, Martin Sillesen
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and pro
Externí odkaz:
https://doaj.org/article/aa3f45fd445f4117b36899935a16679d
Autor:
Daniella Tola, Emil Madsen, Claudio Gomes, Lukas Esterle, Christian Schlette, Casper Hansen, Peter Gorm Larsen
Publikováno v:
Tola, D, Madsen, E, Gomes, C, Esterle, L, Schlette, C, Hansen, C & Larsen, P G 2022, Towards Easy Robot System Integration: Challenges and Future Directions . in 2022 IEEE/SICE International Symposium on System Integration (SII) . IEEE, pp. 77-82, 2022 IEEE/SICE International Symposium on System Integration (SII), Narvik, Norway, 09/01/2022 . https://doi.org/10.1109/SII52469.2022.9708846
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09c2b73e56cfda5a7f6945dc88904f6b
https://doi.org/10.1109/sii52469.2022.9708846
https://doi.org/10.1109/sii52469.2022.9708846
Autor:
Oskar Skak Kristiansen, Ulrik Sandberg, Casper Hansen, Morten Skovgaard Jensen, Jonas Friederich, Sanja Lazarova-Molnar
Publikováno v:
Simulation Tools and Techniques ISBN: 9783030971236
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c2b5b5ee51a27a8376b031853e01f78
https://doi.org/10.1007/978-3-030-97124-3_24
https://doi.org/10.1007/978-3-030-97124-3_24
Publikováno v:
Hansen, C, Tobberup, R, Rasmussen, H H, Delekta, A M & Holst, M 2021, ' Measurement of body composition : Agreement between methods of measurement by bioimpedance and computed tomography in patients with non-small cell lung cancer ', Clinical Nutrition ESPEN, vol. 44, pp. 429-436 . https://doi.org/10.1016/j.clnesp.2021.04.021
BACKGROUND AND AIMS: Cancer cachexia is a muscle wasting syndrome which is promoted by the presence of inflammation and metabolic changes. Cancer cachexia has shown predictable for survival, progression of physical impairment as well as patient-repor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e38eb8f348730302641b5f168da3316
https://vbn.aau.dk/da/publications/3a58ce0a-b2f7-4b88-b0fe-408bca87df2e
https://vbn.aau.dk/da/publications/3a58ce0a-b2f7-4b88-b0fe-408bca87df2e
Publikováno v:
ACL/IJCNLP (2)
Most fact checking models for automatic fake news detection are based on reasoning: given a claim with associated evidence, the models aim to estimate the claim veracity based on the supporting or refuting content within the evidence. When these mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88042de608dd68f28fe4097195796b28
Publikováno v:
Hansen, C, Hansan, C, Simonsen, J G, Alstrup, S & Lioma, C 2020, Content-aware Neural Hashing for Cold-start Recommendation . in SIGIR 2020-Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 971-980, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401060
SIGIR
SIGIR
Content-aware recommendation approaches are essential for providing meaningful recommendations for \textit{new} (i.e., \textit{cold-start}) items in a recommender system. We present a content-aware neural hashing-based collaborative filtering approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19a3fb8eead9a228831ca7f7d0760379
http://arxiv.org/abs/2006.00617
http://arxiv.org/abs/2006.00617
Publikováno v:
Hansen, C, Hansen, C, Simonsen, J G, Alstrup, S & Lioma, C 2020, Unsupervised Semantic Hashing with Pairwise Reconstruction . in SIGIR 2020-Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 2009-2012, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401220
SIGIR
SIGIR
Semantic Hashing is a popular family of methods for efficient similarity search in large-scale datasets. In Semantic Hashing, documents are encoded as short binary vectors (i.e., hash codes), such that semantic similarity can be efficiently computed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ab19b87c6e9bba8c653800d1dc924d8
https://curis.ku.dk/portal/da/publications/unsupervised-semantic-hashing-with-pairwise-reconstruction(d8079968-f1d5-40ae-8372-e0ed073522ca).html
https://curis.ku.dk/portal/da/publications/unsupervised-semantic-hashing-with-pairwise-reconstruction(d8079968-f1d5-40ae-8372-e0ed073522ca).html
Autor:
Jakob Grue Simonsen, Casper Hansen, Christina Lioma, Christian Hansen, Birger Larsen, Stephen Alstrup
Publikováno v:
Hansen, C, Hansen, C, Simonsen, J G, Larsen, B, Alstrup, S & Lioma, C 2020, Factuality Checking in News Headlines with Eye Tracking . in SIGIR 2020-Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 2013-2016, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401221
Hansen, C, Hansen, C, Simonsen, J G, Larsen, B, Alstrup, S & Lioma, C 2020, Factuality Checking in News Headlines with Eye Tracking . in Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 2013-2016, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401221
SIGIR
Hansen, C, Hansen, C, Simonsen, J G, Larsen, B, Alstrup, S & Lioma, C 2020, Factuality Checking in News Headlines with Eye Tracking . in Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval . Association for Computing Machinery, pp. 2013-2016, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25/07/2020 . https://doi.org/10.1145/3397271.3401221
SIGIR
We study whether it is possible to infer if a news headline is true or false using only the movement of the human eyes when reading news headlines. Our study with 55 participants who are eye-tracked when reading 108 news headlines (72 true, 36 false)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57175d835102b49bcd2a2cd2bd3e8791
https://curis.ku.dk/portal/da/publications/factuality-checking-in-news-headlines-with-eye-tracking(007537ed-41d9-48a8-a03c-75ad9030e756).html
https://curis.ku.dk/portal/da/publications/factuality-checking-in-news-headlines-with-eye-tracking(007537ed-41d9-48a8-a03c-75ad9030e756).html
Publikováno v:
SIGIR
Word embeddings predict a word from its neighbours by learning small, dense embedding vectors. In practice, this prediction corresponds to a semantic score given to the predicted word (or term weight). We present a novel model that, given a target wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10fb9f8f3744f8ae0a478dc4926a2111
https://doi.org/10.1145/3331184.3331307
https://doi.org/10.1145/3331184.3331307
Publikováno v:
SIGIR
Fast similarity search is a key component in large-scale information retrieval, where semantic hashing has become a popular strategy for representing documents as binary hash codes. Recent advances in this area have been obtained through neural netwo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36eeedb229b2ac3706a480fadc5f4814
https://doi.org/10.1145/3331184.3331255
https://doi.org/10.1145/3331184.3331255