Zobrazeno 1 - 10
of 1 257
pro vyhledávání: '"Ekart, A."'
Autor:
Varda, Luka1 (AUTHOR) luka.varda@gmail.com, Ekart, Robert1,2 (AUTHOR) robert.ekart2@guest.arnes.si, Lainscak, Mitja3,4 (AUTHOR) mitja.lainscak@guest.arnes.si, Maver, Uroš2,5 (AUTHOR), Bevc, Sebastjan2,6 (AUTHOR) sebastjan.bevc@ukc-mb.si
Publikováno v:
International Journal of Molecular Sciences. Aug2024, Vol. 25 Issue 16, p9088. 21p.
Publikováno v:
BMC Cardiovascular Disorders, Vol 23, Iss 1, Pp 1-9 (2023)
Abstract Background Obesity is associated with several neurohumoral changes that play an essential role in organ damage. Increased arterial stiffness causes functional vessel wall changes and can therefore lead to accelerated target organ damage as w
Externí odkaz:
https://doaj.org/article/e932be495a7f449aa5be85c4bcdd6cdb
Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or gangre
Externí odkaz:
http://arxiv.org/abs/2104.05647
Publikováno v:
International Journal of Molecular Sciences, Vol 25, Iss 16, p 9088 (2024)
Mineralocorticoid receptor antagonists (MRAs) are one of the renin–angiotensin–aldosterone system inhibitors widely used in clinical practice. While spironolactone and eplerenone have a long-standing profile in clinical medicine, finerenone is a
Externí odkaz:
https://doaj.org/article/e2325ee0cd8a48259ea05b37bccca5bf
Autor:
Jantan, Khairil A.1,2 (AUTHOR) khairil0323@uitm.edu.my, Ekart, Gregor1 (AUTHOR) gregor.ekart15@imperial.ac.uk, McCarthy, Sean1 (AUTHOR) c.braddock@imperial.ac.uk, White, Andrew J. P.1 (AUTHOR), Braddock, D. Christopher1 (AUTHOR), Serpe, Angela3 (AUTHOR) serpe@unica.it, Wilton-Ely, James D. E. T.1 (AUTHOR) j.wilton-ely@imperial.ac.uk
Publikováno v:
Catalysts (2073-4344). May2024, Vol. 14 Issue 5, p295. 17p.
In this work, we present the Chatbot Interaction with Artificial Intelligence (CI-AI) framework as an approach to the training of deep learning chatbots for task classification. The intelligent system augments human-sourced data via artificial paraph
Externí odkaz:
http://arxiv.org/abs/2010.05990
The novelty of this study consists in a multi-modality approach to scene classification, where image and audio complement each other in a process of deep late fusion. The approach is demonstrated on a difficult classification problem, consisting of t
Externí odkaz:
http://arxiv.org/abs/2007.10175
In speech recognition problems, data scarcity often poses an issue due to the willingness of humans to provide large amounts of data for learning and classification. In this work, we take a set of 5 spoken Harvard sentences from 7 subjects and consid
Externí odkaz:
http://arxiv.org/abs/2007.00659
The continuous expansion of the urban traffic sensing infrastructure has led to a surge in the volume of widely available road related data. Consequently, increasing effort is being dedicated to the creation of intelligent transportation systems, whe
Externí odkaz:
http://arxiv.org/abs/2002.06095
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.