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Deep learning for building occupancy estimation using environmental sensors

Referentgranskad
DOI
10.1007/978-3-030-31760-7_11
Chen, Zhenghua; Jiang, Chaoyang; Masood, Mustafa K.; Soh, Yeng Chai; Wu, Min; Li, Xiaoli
Studies in Computational Intelligence2020Publicationer information ikon

Contrasting residence time and scavenging communities of experimental invertebrate food falls in the Arctic deep sea

Referentgranskad
Öppen tillgång
DOI
10.1016/j.dsr.2022.103832
Rohlfer, Eva K; Scheer, S.L.; Bergmann, Manuela M; Sweetman, A.K.; Hoving, H.J.T.
Deep-Sea Research. Part 1: Oceanographic Research Papers2022Publicationer information ikon

Hydrogeological characteristics of the Outokumpu Deep Drill Hole

Öppen tillgång
Ahonen, Laura; Kietäväinen, Riikka; Kortelainen, Nina; Kukkonen, Ilmo T.; Pullinen, Arto; Toppi, Tar...
GSF2011Publicationer information ikon

2D and 3D Numerical Analyses of Deep-Stabilized Columns

Referentgranskad
Aalto, A.; Krenn, H.; Karstunen, M.
Swedish Deep Stabilization Research Centre2005Publicationer information ikon

Fennoscandian Shield: A treasure box for deep electromagnetic studies

Korja, T & Hjelt, Sven-Erik
-1998Publicationer information ikon

Microbiological sampling and analysis of the Outokumpu Deep Borehole biosphere in 2007-2008

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Öppen tillgång
Itävaara, Merja; Nyyssönen, Mari; Bomberg, Malin; Kapanen, Anu; Nousiainen, Aura; Ahonen, Lasse; Hul...
Geological Survey of Finland. Special Paper2011Publicationer information ikon

The Digital Twin of an Organization by Utilizing Reinforcing Deep Learning

Referentgranskad
Öppen tillgång
DOI
10.5772/intechopen.96168
Marko Kesti
IntechOpen2021Publicationer information ikon

Benthic foraminifera from the deep-water Niger delta (Gulf of Guinea):Assessing present-day and past activity of hydrate pockmarks

Referentgranskad
Fontanier, C.; Koho, K. A.; Goni-Urriza, M. S.; Deflandre, B.; Galaup, S.; Ivanovsky, A.; Gayet, N.;...
Deep-Sea Research. Part 1: Oceanographic Research Papers2014Publicationer information ikon

Kinship verification based on deep learning

Referentgranskad
DOI
10.1007/978-981-10-5152-4_5
Wu, X.; Feng, X.; Li, L.; Boutellaa, E.; Hadid, A.
Springer2019Publicationer information ikon

RGB and Depth Image Fusion for Object Detection Using Deep Learning

Referentgranskad
DOI
10.1007/978-981-16-3357-7_3
Farahnakian Fahimeh, Heikkonen Jukka
Springer2021

Deep learning for building occupancy estimation using environmental sensors

Referentgranskad
DOI
10.1007/978-3-030-31760-7_11
2020

Contrasting residence time and scavenging communities of experimental invertebrate food falls in the Arctic deep sea

Referentgranskad
Öppen tillgång
DOI
10.1016/j.dsr.2022.103832
2022

Hydrogeological characteristics of the Outokumpu Deep Drill Hole

Öppen tillgång
2011

2D and 3D Numerical Analyses of Deep-Stabilized Columns

Referentgranskad
2005

Fennoscandian Shield: A treasure box for deep electromagnetic studies

1998

Microbiological sampling and analysis of the Outokumpu Deep Borehole biosphere in 2007-2008

Referentgranskad
Öppen tillgång
2011

The Digital Twin of an Organization by Utilizing Reinforcing Deep Learning

Referentgranskad
Öppen tillgång
DOI
10.5772/intechopen.96168
2021

Benthic foraminifera from the deep-water Niger delta (Gulf of Guinea):Assessing present-day and past activity of hydrate pockmarks

Referentgranskad
2014

Kinship verification based on deep learning

Referentgranskad
DOI
10.1007/978-981-10-5152-4_5
2019

RGB and Depth Image Fusion for Object Detection Using Deep Learning

Referentgranskad
DOI
10.1007/978-981-16-3357-7_3
2021