Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Hendrik Schilling"'
Autor:
Norbert Stock, Lars-Hendrik Schilling
Publikováno v:
Acta Crystallographica Section E, Vol 69, Iss 8, Pp m452-m453 (2013)
The structure of the title polymer, }[Mg(C6H14N2O6P2)(H2O)4]·0.5H2O}n, is based on centrosymmetric MgO6 octahedra, which are linked by [(piperazine-1,4-diium-1,4-diyl)bis(methylene)]diphosphonate ligands, forming chains parallel to [1-1-1]. These ch
Externí odkaz:
https://doaj.org/article/fd92dee8747b45afa362b39765abba58
Autor:
Marcel Gutsche, Hendrik Schilling, Alexander Brock, Carsten Rother, Karsten Krispin, Dane Spath
Publikováno v:
CVPR Workshops
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::043b384b5940519d6f9f86ddfcad9630
https://doi.org/10.1109/cvprw50498.2020.00177
https://doi.org/10.1109/cvprw50498.2020.00177
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11:4299-4316
Convolutional neural networks, or CNNs, raised the bar for most computer vision problems and have an increasing impact in remote sensing. However, since they usually contain multiple pooling layers, detection of exact borders of small objects at thei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dfa5b50bfea01d8b227ba354e2c06c0
https://doi.org/10.1109/jstars.2018.2825099
https://doi.org/10.1109/jstars.2018.2825099
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 136:85-105
The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c98f5226edd5394322a7e8aa08da852f
https://doi.org/10.1016/j.isprsjprs.2017.11.023
https://doi.org/10.1016/j.isprsjprs.2017.11.023
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-1-W1, Pp 115-123 (2017)
In recent years, there has been a significant improvement in the detection, identification and classification of objects and images using Convolutional Neural Networks. To study the potential of the Convolutional Neural Network, in this paper three a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1a0233ef9b5dd6e7de1ea655a19ba03
https://doi.org/10.5194/isprs-annals-iv-1-w1-115-2017
https://doi.org/10.5194/isprs-annals-iv-1-w1-115-2017
Publikováno v:
tm - Technisches Messen. 84:440-451
Camera calibration, crucial for computer vision tasks, often relies on planar calibration targets to calibrate the camera parameters. This work describes the design of a planar, fractal, self-identifying calibration pattern, which provides a high den
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ce31a45b088b0d1cbc7a090619ef3b1
https://doi.org/10.1515/teme-2017-0013
https://doi.org/10.1515/teme-2017-0013
Publikováno v:
3DV
We propose a method for depth estimation from light field data, based on a fully convolutional neural network architecture. Our goal is to design a pipeline which achieves highly accurate results for small- and wide-baseline light fields. Since light
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24789e0f1b53d85ddbbfaa8f792c2a8b
Autor:
Maximilian Diebold, Marcel Gutsche, Anna Alperovich, Ole Johannsen, Shuo Zhang, Jaesik Park, Marco Carli, Michele Brizzi, Hae-Gon Jeon, Yu-Wing Tai, Sven Wanner, Bastian Goldluecke, Jinsun Park, Yunsu Bok, Zhang Xiong, Hao Sheng, Jingyi Yu, Qing Wang, Lipeng Si, Katrin Honauer, In So Kweon, Antonin Sulc, Gyeongmin Choe, Michael Strecke, Hendrik Schilling, Hao Zhu, Federica Battisti, Ting-Chun Wang
Publikováno v:
CVPR Workshops
This paper presents the results of the depth estimation challenge for dense light fields, which took place at the second workshop on Light Fields for Computer Vision (LF4CV) in conjunction with CVPR 2017. The challenge consisted of submission to a re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ffa868510b01306b9d4840d36d0d24d
http://hdl.handle.net/11577/3363391
http://hdl.handle.net/11577/3363391
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B3, Pp 575-582 (2016)
In this paper, a new procedure for individual tree detection and modeling is presented. The input of this procedure consists of a normalized digital surface model NDSM, and a possibly error-prone classification result. The procedure is modular so tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13930a774d1c48b199d42bc63aad8084
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/575/2016/isprs-archives-XLI-B3-575-2016.pdf
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/575/2016/isprs-archives-XLI-B3-575-2016.pdf
Publikováno v:
Earth Resources and Environmental Remote Sensing/GIS Applications IX.
Semantic land cover classification of satellite images or airborne images is becoming increasingly important for applications like urban planning, road net analysis or environmental monitoring. Sensor orientations or varying illumination make classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57449cf1766d0923ff141cb215a6c1d9
https://doi.org/10.1117/12.2325604
https://doi.org/10.1117/12.2325604