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pro vyhledávání: '"Wetzer, Elisabeth"'
Multimodal imaging and correlative analysis typically require image alignment. Contrastive learning can generate representations of multimodal images, reducing the challenging task of multimodal image registration to a monomodal one. Previously, addi
Externí odkaz:
http://arxiv.org/abs/2303.00403
In tissue characterization and cancer diagnostics, multimodal imaging has emerged as a powerful technique. Thanks to computational advances, large datasets can be exploited to discover patterns in pathologies and improve diagnosis. However, this requ
Externí odkaz:
http://arxiv.org/abs/2201.03597
Autor:
Breznik, Eva1,2, Wetzer, Elisabeth1,3 elisabeth.wetzer@uit.no, Lindblad, Joakim1, Sladoje, Nataša1
Publikováno v:
Scientific Reports. 8/13/2024, Vol. 14 Issue 1, p1-12. 12p.
Autor:
Pielawski, Nicolas, Wetzer, Elisabeth, Öfverstedt, Johan, Lu, Jiahao, Wählby, Carolina, Lindblad, Joakim, Sladoje, Nataša
Publikováno v:
NeurIPS 2020
We propose contrastive coding to learn shared, dense image representations, referred to as CoMIRs (Contrastive Multimodal Image Representations). CoMIRs enable the registration of multimodal images where existing registration methods often fail due t
Externí odkaz:
http://arxiv.org/abs/2006.06325
Publikováno v:
International Wound Journal; Jul2024, Vol. 21 Issue 7, p1-12, 12p
Autor:
Wetzer, Elisabeth
In recent years Machine Learning and in particular Deep Learning have excelled in object recognition and classification tasks in computer vision. As these methods extract features from the data itself by learning features that are relevant for a part
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______361::8ec59ce7a88ee7342a6502de23f0b5cb
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-500386
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-500386
Autor:
Wetzer, Elisabeth
Das Ziel dieser Studie besteht darin, die Realisierbarkeit eines neuen Ansatzes zur automatisierten Fasernanalyse mittels Raman-Spektroskopie zu evaluieren. Um eine automatisch gesteuerte Kollektion von Raman-Spektren zu erm��glichen, besch��
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e45dac089ab127b185ce4745d8480cf