Zobrazeno 1 - 10
of 192
pro vyhledávání: '"J, Tax"'
Autor:
Michiel Bongaerts, Purva Kulkarni, Alan Zammit, Ramon Bonte, Leo A. J. Kluijtmans, Henk J. Blom, Udo F. H. Engelke, David M. J. Tax, George J. G. Ruijter, Marcel J. T. Reinders
Publikováno v:
Metabolites, Vol 13, Iss 1, p 97 (2023)
Untargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detec
Externí odkaz:
https://doaj.org/article/55277592bb904597a726162336280ba9
Publikováno v:
ACM Proceedings on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5(1)
Human head orientation estimation has been of interest because head orientation serves as a cue to directed social attention. Most existing approaches rely on visual and high-fidelity sensor inputs and deep learning strategies that do not consider th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c24e8865ff63a7e121b374ecedd48af8
https://doi.org/10.1145/3448122
https://doi.org/10.1145/3448122
Publikováno v:
IEEE Transactions on Image Processing, 29
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
The main challenges of age estimation from facial expression videos lie not only in the modeling of the static facial appearance, but also in the capturing of the temporal facial dynamics. Traditional techniques to this problem focus on constructing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96765133798d9426dbcab618e210c73f
https://doi.org/10.1109/tip.2019.2948288
https://doi.org/10.1109/tip.2019.2948288
Publikováno v:
Nonlinear Processes in Geophysics, Vol 15, Iss 6, Pp 863-871 (2008)
Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding
Externí odkaz:
https://doaj.org/article/4b80d838ecd141828bb22be2be95d0d0
Autor:
Martin A Rijlaarsdam, David M J Tax, Ad J M Gillis, Lambert C J Dorssers, Devin C Koestler, Jeroen de Ridder, Leendert H J Looijenga
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0122146 (2015)
The cell of origin of the five subtypes (I-V) of germ cell tumors (GCTs) are assumed to be germ cells from different maturation stages. This is (potentially) reflected in their methylation status as fetal maturing primordial germ cells are globally d
Externí odkaz:
https://doaj.org/article/975d06688b5f45f1be1ab937fde9af10
Publikováno v:
Pattern Recognition Letters. 128:231-236
We study the problem of Protein Remote Homology Detection, which assesses the functional similarity of two proteins. We approach this as a problem of binary multiple-instance learning (MIL) that aims to distinguish between homologous and non-homologo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1795e55910650aeddf5d7936336fc733
https://doi.org/10.1016/j.patrec.2019.08.027
https://doi.org/10.1016/j.patrec.2019.08.027
Publikováno v:
Pattern Recognition Letters. 125:310-317
Learning probability densities for natural language representations is a difficult problem because language is inherently sparse and high-dimensional. Negative sampling is a popular and effective way to avoid intractable maximum likelihood problems,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5518c5e9b45f1d105458f3611254351a
https://doi.org/10.1016/j.patrec.2019.04.027
https://doi.org/10.1016/j.patrec.2019.04.027
Autor:
David M. J. Tax, Veronica Tollenaar, Vinciane Debaille, Harry Zekollari, Steven Goderis, Philippe Claeys, Frank Pattyn, Stef Lhermitte
Meteorites provide an unparalleled view on the origin and evolution of the solar system. Antarctica is the most productive region for collecting meteorites, as the visually contrasting meteorites are easily detectable and tend to concentrate at speci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89786e2e7eee88c14c50a5d1b353a5f1
https://doi.org/10.5194/egusphere-egu21-9530
https://doi.org/10.5194/egusphere-egu21-9530
Publikováno v:
ICPR
Isolation Forests are a very successful approach for solving outlier detection tasks. Isolation Forests are based on classical Random Forest classifiers that require feature vectors as input. There are many situations where vectorial data is not read
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bb8cd8876c90256191ae9407a38dce7
https://doi.org/10.1109/icpr48806.2021.9412322
https://doi.org/10.1109/icpr48806.2021.9412322
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030739720
S+SSPR
S+SSPR
Isolation Forests are one of the most successful outlier detection techniques: they isolate outliers by performing random splits in each node. It has been recently shown that a trained Random Forest-based model can also be used to define and extract
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9a24e42d173d646df56f8923801bfbf
https://doi.org/10.1007/978-3-030-73973-7_4
https://doi.org/10.1007/978-3-030-73973-7_4