Zobrazeno 1 - 10
of 10 083
pro vyhledávání: '"[ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG]"'
Autor:
Ariane Pinche, Peter Stokes
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol Historical Documents and... (2024)
With this special issue of the Journal of Data Mining and Digital Humanities (JDMDH), we bringtogether in one single volume several experiments, projects and reflections related to automatic textrecognition applied to historical documents. More and m
Externí odkaz:
https://doaj.org/article/0aa874c87b904ad2a6b793699d0b0b80
Autor:
Ariane Pinche
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol Historical Documents and... (2023)
In the Humanities, the emergence of digital methods has opened up research questions to quantitative analysis. This is why HTR technology is increasingly involved in humanities research projects following precursors such as the Himanis project. Howev
Externí odkaz:
https://doaj.org/article/d8b5d0bf413f4f90a9d62b3c2ff02c2f
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol 2022 (2022)
This paper presents a model aiming to automatically detect sections in medieval Latin charters. These legal sources are some of the most important sources for medieval studies as they reflect economic and social dynamics as well as legal and institut
Externí odkaz:
https://doaj.org/article/e132e0261a234ff29e83caff5263f580
Publikováno v:
Proceedings on Privacy Enhancing Technologies
Proceedings on Privacy Enhancing Technologies, In press, 2023 (2)
Proceedings on Privacy Enhancing Technologies, In press, 2023 (2)
International audience; In this paper we study verifiable sampling from probability distributions in the context of multi-party computation. This has various applications in randomized algorithms performed collaboratively by parties not trusting each
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c6cec17699bdde07abf758ca777f5f1
https://doi.org/10.56553/popets-2023-0058
https://doi.org/10.56553/popets-2023-0058
Publikováno v:
Journal of the Korean Statistical Society. 52:154-184
The determination of the number of mixture components (the order) of a finite mixture model has been an enduring problem in statistical inference. We prove that the closed testing principle leads to a sequential testing procedure (STP) that allows fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d7396cb4d1f4fc74ffb1da989ce7c0b
https://doi.org/10.1007/s42952-022-00195-z
https://doi.org/10.1007/s42952-022-00195-z
Publikováno v:
IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, 2022, 41 (10), pp.2867-2878. ⟨10.1109/TMI.2022.3173669⟩
IEEE Transactions on Medical Imaging, 2022, 41 (10), pp.2867-2878. ⟨10.1109/TMI.2022.3173669⟩
Convolutional neural networks (CNN) have demonstrated their ability to segment 2D cardiac ultrasound images. However, despite recent successes according to which the intra-observer variability on end-diastole and end-systole images has been reached,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::348268feae255c78f396f89abd83e66d
https://doi.org/10.1109/tmi.2022.3173669
https://doi.org/10.1109/tmi.2022.3173669
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol HistoInformatics, Iss HistoInformatics (2021)
Identifying, contacting and engaging missing shareholders constitutes an enormous challenge for Māori incorporations, iwi and hapū across Aotearoa New Zealand. Without accurate data or tools to har-monise existing fragmented or conflicting data sou
Externí odkaz:
https://doaj.org/article/0504d86854b64d06acff05dbf521eb41
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol HistoInformatics, Iss HistoInformatics (2021)
Many libraries offer free access to digitised historical newspapers via user interfaces. After an initial period of search and filter options as the only features, the availability of more advanced tools and the desire for more options among users ha
Externí odkaz:
https://doaj.org/article/467be3bc585e416b9dbcf0f389d0e9d9
Autor:
Julien Duquesne, Vincent Bouget, Paul Henry Cournède, Bruno Fautrel, Francis Guillemin, Pascal H P de Jong, Judith W Heutz, Marloes Verstappen, Annette H M van der Helm-van Mil, Xavier Mariette, Samuel Bitoun
Publikováno v:
Rheumatology
Rheumatology, 2023, ⟨10.1093/rheumatology/keac645⟩
Rheumatology. OXFORD UNIV PRESS
Rheumatology, 2023, ⟨10.1093/rheumatology/keac645⟩
Rheumatology. OXFORD UNIV PRESS
Objectives Around 30% of patients with RA have an inadequate response to MTX. We aimed to use routine clinical and biological data to build machine learning models predicting EULAR inadequate response to MTX and to identify simple predictive biomarke
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f62b582b03f120eb45301dc044f2965d
https://hal.science/hal-03986625/file/3071.pdf
https://hal.science/hal-03986625/file/3071.pdf
Autor:
Annachiara Ruospo, Ernesto Sanchez, Lucas Matana Luza, Luigi Dilillo, Marcello Traiola, Alberto Bosio
Publikováno v:
Computer
Computer, 2023, 56, pp.57-66. ⟨10.1109/MC.2022.3217841⟩
Computer, 2023, 56, pp.57-66. ⟨10.1109/MC.2022.3217841⟩
International audience; Deep Learning (DL) applications are gaining increasing interest in the industry and academia for their outstanding computational capabilities. Indeed, they have found successful applications in various areas and domains such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe77c451d906e07fc429717fa472b3c3
https://doi.org/10.1109/mc.2022.3217841
https://doi.org/10.1109/mc.2022.3217841