Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Gottfried Schwarz"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 9223-9230 (2023)
Quantum machine learning (QML) models promise to have some computational (or quantum) advantage for classifying supervised datasets (e.g., satellite images) over some conventional deep learning (DL) techniques due to their expressive power via their
Externí odkaz:
https://doaj.org/article/27896af76fe745ea9fbe1964a4c8ed67
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 676-689 (2021)
In this article, we propose a promising approach for the application-oriented content classification of spaceborne radar imagery that presents an interesting alternative to popular current machine learning algorithms. In the following, we consider th
Externí odkaz:
https://doaj.org/article/d72606e93aa94f2b9fb7cff5960c04e7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 6009-6068 (2021)
While the analysis and understanding of multispectral (i.e., optical) remote sensing images have made considerable progress during the last decades, the automated analysis of synthetic aperture radar (SAR) satellite images still needs some innovative
Externí odkaz:
https://doaj.org/article/47d5c4e9ae674048ad759048b7444663
Autor:
Corneliu Octavian Dumitru, Gottfried Schwarz, Anna Pulak-Siwiec, Bartosz Kulawik, Mohanad Albughdadi, Jose Lorenzo, Mihai Datcu
Publikováno v:
Big Earth Data, Vol 4, Iss 4, Pp 367-408 (2020)
The increased number of free and open Sentinel satellite images has led to new applications of these data. Among them is the systematic classification of land cover/use types based on patterns of settlements or agriculture recorded by these images, i
Externí odkaz:
https://doaj.org/article/810ad65a23594dd2a85c64e39abc73bb
Autor:
Mihai Datcu, Alexandru-Cosmin Grivei, Daniela Espinoza-Molina, Corneliu Octavian Dumitru, Christoph Reck, Vlad Manilici, Gottfried Schwarz
Publikováno v:
Big Earth Data, Vol 4, Iss 3, Pp 265-294 (2020)
Throughout the years, various Earth Observation (EO) satellites have generated huge amounts of data. The extraction of latent information in the data repositories is not a trivial task. New methodologies and tools, being capable of handling the size,
Externí odkaz:
https://doaj.org/article/0274c86eabbf4851bbf43ac8028f1a3d
Publikováno v:
Remote Sensing, Vol 10, Iss 10, p 1597 (2018)
With more and more SAR applications, the demand for enhanced high-quality SAR images has increased considerably. However, high-quality SAR images entail high costs, due to the limitations of current SAR devices and their image processing resources. T
Externí odkaz:
https://doaj.org/article/8c2bd910e3544d49bc9da1a5e18c888d
The European Copernicus Sentinel-1 SAR mission offers a unique chance to compare and analyse long time series of freely accessible SAR images with frequent coverage in the northern polar areas. In our case, during the ExtremeEarth project (H2020 gran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ea1b2130a9c692b171e19023e7ecb65
https://doi.org/10.5194/egusphere-egu23-452
https://doi.org/10.5194/egusphere-egu23-452
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2021, Pp 455-462 (2021)
When we want to extract knowledge form satellite images, several well-known image classification and analysis techniques can be concatenated or combined to gain a more detailed target understanding. In our case, we concentrated on specific extended t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::085f5ed945cd750c686e760ed8033ca2
https://doi.org/10.5194/isprs-archives-xliii-b3-2021-455-2021
https://doi.org/10.5194/isprs-archives-xliii-b3-2021-455-2021
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-2-W16, Pp 83-89 (2019)
ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Today, radar imaging from space allows continuous and wide-area sea ice monitoring under nearly all weather conditions. To this end, we applied modern machine learning techniques to produce ice-describing semantic maps of the polar regions of the Ear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fda7bcc78bce8a4ef896a340515d725a
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W16/83/2019/isprs-archives-XLII-2-W16-83-2019.pdf
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W16/83/2019/isprs-archives-XLII-2-W16-83-2019.pdf
Autor:
Octavian Dumitru, Zhongling Huang, Mila Stillman, Gottfried Schwarz, Dongyang Ao, Mihai Datcu
During the last years, much progress has been reached with machine learning algorithms. Among the typical application fields of machine learning are many technical and commercial applications as well as Earth science analyses, where most often indire
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63c7883dad826fed45ba9cbf1b5ce0ad
https://doi.org/10.5194/egusphere-egu21-4683
https://doi.org/10.5194/egusphere-egu21-4683