Zobrazeno 1 - 10
of 42
pro vyhledávání: '"RGB sensors"'
Autor:
François Dupont, Serguei Stoukatch, Philippe Laurent, Kasper Eersels, Bart van Grinsven, Jean-Michel Redouté
Publikováno v:
Sensors, Vol 24, Iss 6, p 1960 (2024)
Colorimetric characterisation systems based on LEDs and RBG sensors are straightforward to implement, are highly integrable allowing for portable measurement systems and can be constructed using widespread and affordable components. They have already
Externí odkaz:
https://doaj.org/article/1c4360b5664b462ab937d2faadbde0f3
Publikováno v:
Agriculture, Vol 13, Iss 3, p 707 (2023)
Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study foc
Externí odkaz:
https://doaj.org/article/8a7f2169e7604b5eb802f100f07e635d
Akademický článek
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Autor:
Ko Watanabe, Yusuke Soneda, Yuki Matsuda, Yugo Nakamura, Yutaka Arakawa, Andreas Dengel, Shoya Ishimaru
Publikováno v:
Sensors, Vol 21, Iss 17, p 5719 (2021)
The emergence of various types of commercial cameras (compact, high resolution, high angle of view, high speed, and high dynamic range, etc.) has contributed significantly to the understanding of human activities. By taking advantage of the character
Externí odkaz:
https://doaj.org/article/003609abb6df406c9935ea9c680d3025
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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K zobrazení výsledku je třeba se přihlásit.
Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study foc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5cf36b05b00b4ac307b700af4689d8d
https://doi.org/10.3390/agriculture13030707
https://doi.org/10.3390/agriculture13030707
Autor:
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Sergio A. Velastin, and Pablo Zegers
Publikováno v:
Sensors, Vol 20, Iss 7, p 1825 (2020)
We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB sensors using simple cameras. The approach proceeds along two stages. In the first, a real-time 2D pose detector is run to determi
Externí odkaz:
https://doaj.org/article/01f92476c3f64c828d4ad9dfdf229748
Autor:
Alejandro Sánchez de Miguel, Salvador Bará, Martin Aubé, Nicolás Cardiel, Carlos E. Tapia, Jaime Zamorano, Kevin J. Gaston
Publikováno v:
Journal of Imaging, Vol 5, Iss 4, p 49 (2019)
Night-time lights interact with human physiology through different pathways starting at the retinal layers of the eye; from the signals provided by the rods; the S-, L- and M-cones; and the intrinsically photosensitive retinal ganglion cells (ipRGC).
Externí odkaz:
https://doaj.org/article/a85b21c7092f4026a96bd2757975a1cc
Autor:
Andreas Dengel, Yuki Matsuda, Ko Watanabe, Yusuke Soneda, Shoya Ishimaru, Yugo Nakamura, Yutaka Arakawa
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 17
Sensors, Vol 21, Iss 5719, p 5719 (2021)
Sensors
Volume 21
Issue 17
Sensors, Vol 21, Iss 5719, p 5719 (2021)
The emergence of various types of commercial cameras (compact, high resolution, high angle of view, high speed, and high dynamic range, etc.) has contributed significantly to the understanding of human activities. By taking advantage of the character
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9471a96267d911b7346ab4ca3679aa36
https://pubmed.ncbi.nlm.nih.gov/34502609
https://pubmed.ncbi.nlm.nih.gov/34502609
Autor:
Houssam Salmane, Sergio A. Velastin, Pablo Zegers, Louahdi Khoudour, Huy Hieu Pham, Alain Crouzil
Publikováno v:
Sensors (Basel, Switzerland)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Sensors
Sensors, MDPI, 2020, 20 (7), pp.1-15. ⟨10.3390/s20071825⟩
Volume 20
Issue 7
Sensors, Vol 20, Iss 7, p 1825 (2020)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Sensors
Sensors, MDPI, 2020, 20 (7), pp.1-15. ⟨10.3390/s20071825⟩
Volume 20
Issue 7
Sensors, Vol 20, Iss 7, p 1825 (2020)
We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB sensors using simple cameras. The approach proceeds along two stages. In the first, a real-time 2D pose detector is run to determi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2896c65f672b5e9236ba480b7a170098
https://pubmed.ncbi.nlm.nih.gov/32218350
https://pubmed.ncbi.nlm.nih.gov/32218350