Zobrazeno 1 - 10
of 1 434
pro vyhledávání: '"A. Kreidl"'
Autor:
Gultepe, Eren, Wang, Sen, Blomquist, Byron, Fernando, Harindra J. S., Kreidl, O. Patrick, Delene, David J., Gultepe, Ismail
Publikováno v:
Tackling Climate Change with Machine Learning: workshop at NeurIPS 2023
This study presents the application of generative deep learning techniques to evaluate marine fog visibility nowcasting using the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations collected during July 2022 in th
Externí odkaz:
http://arxiv.org/abs/2402.06800
Autor:
Matloob, Samuel, Datta, Partha P., Kreidl, O. Patrick, Dutta, Ayan, Roy, Swapnoneel, Bölöni, Ladislau
Recent developments in robotic and sensor hardware make data collection with mobile robots (ground or aerial) feasible and affordable to a wide population of users. The newly emergent applications, such as precision agriculture, weather damage assess
Externí odkaz:
http://arxiv.org/abs/2305.06243
Autor:
Kreidl, Martin, Hubatková, Barbora
Publikováno v:
Demographic Research, 2023 Jul 01. 49, 635-650.
Externí odkaz:
https://www.jstor.org/stable/48754919
Autor:
Katalin Zboray, Adam V. Toth, Tímea D. Miskolczi, Krisztina Pesti, Emilio Casanova, Emanuel Kreidl, Arpad Mike, Áron Szenes, László Sági, Peter Lukacs
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Agriculturally important crop plants emit a multitude of volatile organic compounds (VOCs), which are excellent indicators of their health status and their interactions with pathogens and pests. In this study, we have developed a novel cellu
Externí odkaz:
https://doaj.org/article/bde1dc84b033479086f28e42e35f79aa
Autor:
Kreidl, Martin, Žilinčíková, Zuzana
Publikováno v:
Demographic Research, 2023 Jan 01. 48, 641-680.
Externí odkaz:
https://www.jstor.org/stable/48728218
Autor:
Eren Gultepe, Sen Wang, Byron Blomquist, Harindra J. S. Fernando, O. Patrick Kreidl, David J. Delene, Ismail Gultepe
Publikováno v:
Frontiers in Earth Science, Vol 11 (2024)
Introduction: This study presents the application of machine learning (ML) to evaluate marine fog visibility conditions and nowcasting of visibility based on the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations
Externí odkaz:
https://doaj.org/article/bc77c811d2f04f0885801696b61d33f9
Autor:
Trávníčková, Marcela, Kreidl, Martin
Publikováno v:
Sociologický časopis / Czech Sociological Review / Sociologicky casopis / Czech Sociological Review. 59(1):3-30
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1105345
Autor:
Krystal Sides, Grentina Kilungeja, Matthew Tapia, Patrick Kreidl, Benjamin H. Brinkmann, Mona Nasseri
Publikováno v:
Frontiers in Network Physiology, Vol 3 (2023)
This study aims to identify the most significant features in physiological signals representing a biphasic pattern in the menstrual cycle using circular statistics which is an appropriate analytic method for the interpretation of data with a periodic
Externí odkaz:
https://doaj.org/article/5ac1eb9890b24c40897366c9dcc80919
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