Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Markus U. Müller"'
Autor:
Hanna Meyer, Marwan Katurji, Tim Appelhans, Markus U. Müller, Thomas Nauss, Pierre Roudier, Peyman Zawar-Reza
Publikováno v:
Remote Sensing, Vol 8, Iss 9, p 732 (2016)
Spatial predictions of near-surface air temperature ( T a i r ) in Antarctica are required as baseline information for a variety of research disciplines. Since the network of weather stations in Antarctica is sparse, remote sensing methods have large
Externí odkaz:
https://doaj.org/article/c94f7d487e784b92bfc61d75361bc1ec
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol V-1-2020, Pp 33-40 (2020)
Super-resolution aims at increasing image resolution by algorithmic means and has progressed over the recent years due to advances in the fields of computer vision and deep learning. Convolutional Neural Networks based on a variety of architectures h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e630881045b7a4e68b28a80c341ad26e
https://doi.org/10.5194/isprs-annals-v-1-2020-33-2020
https://doi.org/10.5194/isprs-annals-v-1-2020-33-2020
Autor:
Peyman Zawar-Reza, Tim Appelhans, Marwan Katurji, Hanna Meyer, Pierre Roudier, Thomas Nauss, Markus U. Müller
Publikováno v:
Remote Sensing
Volume 8
Issue 9
Pages: 732
Remote Sensing, Vol 8, Iss 9, p 732 (2016)
Volume 8
Issue 9
Pages: 732
Remote Sensing, Vol 8, Iss 9, p 732 (2016)
Spatial predictions of near-surface air temperature ( T a i r ) in Antarctica are required as baseline information for a variety of research disciplines. Since the network of weather stations in Antarctica is sparse, remote sensing methods have large
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b653234cca6343953c070d9375cc500e
https://doi.org/10.3390/rs8090732
https://doi.org/10.3390/rs8090732
Publikováno v:
Journal of Applied Remote Sensing. 9:095984
A light detection and ranging canopy height model (CHM) was used as training data for a segment-based classification of woody patches. The classifier is accurate (∼92%) and suitable for use at the national scale. Height thresholds and percentage co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bf0e62f4a93d490141504488d949de6
https://doi.org/10.1117/1.jrs.9.095984
https://doi.org/10.1117/1.jrs.9.095984