Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Conrad M. Albrecht"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4833-4845 (2023)
We propose a tree-level biomass estimation model approximating allometric equations by LiDAR data. Since tree crown diameter estimation is challenging from spaceborne LiDAR measurements, we develop a model to correlate tree height with biomass on the
Externí odkaz:
https://doaj.org/article/b639b1e58ce4429293c95c5c961fd163
Autor:
Conrad M. Albrecht, Rui Zhang, Xiaodong Cui, Marcus Freitag, Hendrik F. Hamann, Levente J. Klein, Ulrich Finkler, Fernando Marianno, Johannes Schmude, Norman Bobroff, Wei Zhang, Carlo Siebenschuh, Siyuan Lu
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 9, Iss 7, p 427 (2020)
The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the lat
Externí odkaz:
https://doaj.org/article/0c0169512d7344fda291e7659d600141
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 321-336 (2025)
Self-supervised learning guided by masked image modeling, such as masked autoencoder (MAE), has attracted wide attention for pretraining vision transformers in remote sensing. However, MAE tends to excessively focus on pixel details, limiting the mod
Externí odkaz:
https://doaj.org/article/ad141a7704a940acb0a37173d5a8ed62
In deep learning research, self-supervised learning (SSL) has received great attention triggering interest within both the computer vision and remote sensing communities. While there has been a big success in computer vision, most of the potential of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6143d1083493fea12da3cafff1083460
http://arxiv.org/abs/2206.13188
http://arxiv.org/abs/2206.13188
Autor:
Rui Zhang, Johannes Schmude, Levente Klein, Bruce G. Elmegreen, Ildar Khabibrakhmanov, Fernando J. Marianno, Siyuan Lu, Hendrik F. Hamann, Marcus Freitag, Xiaoyan Shao, Carlo Siebenschuh, Conrad M. Albrecht, N. Bobroff
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-3-W12-2020, Pp 255-260 (2020)
In this paper we benchmark a previously introduced big data platform that enables the analysis of big data from remote sensing and other geospatial-temporal data. The platform, called IBM PAIRS Geoscope, has been developed by leveraging open source b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fb11899270e7e3ad0dbc2495b5a54ff
https://doi.org/10.5194/isprs-archives-xlii-3-w12-2020-255-2020
https://doi.org/10.5194/isprs-archives-xlii-3-w12-2020-255-2020
Dear Helmholtz family: The past decade told an exciting success story of machine intelligence. We witnessed computing systems interact with champions in games such as Jeopardy! and Go. Inspired by human creativity, Artificial Intelligence rocks the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::067b0eba0aeb7fb2be2dbc2a1323b378
Autor:
Rui Zhang, Fernando J. Marianno, Levente Klein, Norman Bobroff, Ulrich Finkler, Conrad M. Albrecht, Siyuan Lu, Marcus Freitag, Johannes Schmude, Wei Zhang, Xiaodong Cui, Carlo Siebenschuh, Hendrik F. Hamann
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 9, Iss 427, p 427 (2020)
ISPRS International Journal of Geo-Information
Volume 9
Issue 7
ISPRS International Journal of Geo-Information
Volume 9
Issue 7
The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the lat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe841d425b655c95d620db5545a0df85
https://www.mdpi.com/2220-9964/9/7/427
https://www.mdpi.com/2220-9964/9/7/427
Autor:
Siyuan Lu, Conrad M. Albrecht, Rui Zhang, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David S. Kung
Publikováno v:
KDD
Accurately and globally mapping human infrastructure is an important and challenging task with applications in routing, regulation compliance monitoring, and natural disaster response management etc.. In this paper we present progress in developing a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f098ae721b70b0c9d6e52ceecb13eea7
http://arxiv.org/abs/2005.10053
http://arxiv.org/abs/2005.10053
Publikováno v:
IEEE BigData
We present an efficient clustering algorithm applicable to one-dimensional data such as e.g. a series of timestamps. Given an expected frequency $\Delta T^{-1}$, we introduce an $\mathcal{O}(N)$-efficient method of characterizing $N$ events represent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b435da54ffa7922be18f5ebe5115d28
http://arxiv.org/abs/2004.02089
http://arxiv.org/abs/2004.02089