| 000 | 05444naaaa2201249uu 4500 | ||
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| 001 | https://directory.doabooks.org/handle/20.500.12854/81174 | ||
| 005 | 20220714172042.0 | ||
| 020 | _abooks978-3-0365-3489-3 | ||
| 020 | _a9783036534909 | ||
| 020 | _a9783036534893 | ||
| 024 | 7 |
_a10.3390/books978-3-0365-3489-3 _cdoi |
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| 041 | 0 | _aEnglish | |
| 042 | _adc | ||
| 072 | 7 |
_aTB _2bicssc |
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| 072 | 7 |
_aTBX _2bicssc |
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| 100 | 1 |
_aLehtola, Ville _4edt _91586620 |
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| 700 | 1 |
_aNüchter, Andreas _4edt _91586621 |
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| 700 | 1 |
_aGoulette, François _4edt _91586622 |
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| 700 | 1 |
_aLehtola, Ville _4oth _91586620 |
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| 700 | 1 |
_aNüchter, Andreas _4oth _91586621 |
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| 700 | 1 |
_aGoulette, François _4oth _91586622 |
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| 245 | 1 | 0 | _aAdvances in Mobile Mapping Technologies |
| 260 |
_aBasel _bMDPI - Multidisciplinary Digital Publishing Institute _c2022 |
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| 300 | _a1 electronic resource (268 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
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| 520 | _aMobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. It consists of works introducing a new mobile mapping dataset ('Paris CARLA 3D'), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc _4https://creativecommons.org/licenses/by/4.0/ |
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| 546 | _aEnglish | ||
| 650 | 7 |
_aTechnology: general issues _2bicssc _9928609 |
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| 650 | 7 |
_aHistory of engineering & technology _2bicssc _91129967 |
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| 653 | _aLiDAR | ||
| 653 | _aRetinaNet | ||
| 653 | _ainception | ||
| 653 | _aMobile Laser Scanning | ||
| 653 | _apoint clouds | ||
| 653 | _adata fusion | ||
| 653 | _aLidar | ||
| 653 | _apoint cloud density | ||
| 653 | _apoint cloud coverage | ||
| 653 | _amobile mapping systems | ||
| 653 | _a3D simulation | ||
| 653 | _aPandar64 | ||
| 653 | _aOuster OS-1-64 | ||
| 653 | _amobile laser scanning | ||
| 653 | _alever arm | ||
| 653 | _aboresight angles | ||
| 653 | _aplane-based calibration field | ||
| 653 | _aconfiguration analysis | ||
| 653 | _aaccuracy | ||
| 653 | _acontrollability | ||
| 653 | _aevaluation | ||
| 653 | _acontrol points | ||
| 653 | _aTLS reference point clouds | ||
| 653 | _avisual-inertial odometry | ||
| 653 | _aHelmert variance component estimation | ||
| 653 | _aline feature matching method | ||
| 653 | _acorrelation coefficient | ||
| 653 | _apoint and line features | ||
| 653 | _amobile mapping | ||
| 653 | _amanhole cover | ||
| 653 | _apoint cloud | ||
| 653 | _aF-CNN | ||
| 653 | _atransfer learning | ||
| 653 | _aCAM localization | ||
| 653 | _aloop closure detection | ||
| 653 | _avisual SLAM | ||
| 653 | _asemantic topology graph | ||
| 653 | _agraph matching | ||
| 653 | _aCNN features | ||
| 653 | _adeep learning | ||
| 653 | _aview planning | ||
| 653 | _aimaging network design | ||
| 653 | _abuilding 3D modelling | ||
| 653 | _apath planning | ||
| 653 | _aV-SLAM | ||
| 653 | _areal-time | ||
| 653 | _aguidance | ||
| 653 | _aembedded-systems | ||
| 653 | _a3D surveying | ||
| 653 | _aexposure control | ||
| 653 | _aphotogrammetry | ||
| 653 | _aparking statistics | ||
| 653 | _avehicle detection | ||
| 653 | _arobot operating system | ||
| 653 | _a3D camera | ||
| 653 | _aRGB-D | ||
| 653 | _aperformance evaluation | ||
| 653 | _aconvolutional neural networks | ||
| 653 | _asmart city | ||
| 653 | _ageoreferencing | ||
| 653 | _aMSS | ||
| 653 | _aIEKF | ||
| 653 | _aDSIEKF | ||
| 653 | _ageometrical constraints | ||
| 653 | _a6-DoF | ||
| 653 | _aDTM | ||
| 653 | _a3D city model | ||
| 653 | _adataset | ||
| 653 | _alaser scanning | ||
| 653 | _a3D mapping | ||
| 653 | _asynthetic | ||
| 653 | _aoutdoor | ||
| 653 | _asemantic | ||
| 653 | _ascene completion | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/5205 _70 _zDOAB: download the publication |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/81174 _70 _zDOAB: description of the publication |
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