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A Feature Level Multi-Sensor Information Fusion Strategy fo..:

, In: 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR),

Schierl, Jonathan ; Asari, Vijayan ; Singer, Nina... - p. 1-7 , 2021

Link: https://doi.org/10.1109/AIPR52630.2021.9762086

RT 
T1 <cTitle>2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)</cTitle>: T1 <Title>A Feature Level Multi-Sensor Information Fusion Strategy for Land Region Classification</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-9762086&Exemplar=1&LAN=DE
				
A1 Schierl, Jonathan
A1 Asari, Vijayan
A1 Singer, Nina
A1 Aspiras, Theus
A1 Stokes, Andrew
A1 Keaffaber, Brett
A1 Van Rynbach, Andre
A1 Decker, Kevin
A1 Rabb, David
YR 2021
SN 2332-5615
K1 Deep learning
K1 Three-dimensional displays
K1 Laser radar
K1 Image recognition
K1 Target recognition
K1 Surveillance
K1 Urban planning
K1 lidar
K1 aerial imagery
K1 fusion
K1 point clouds
K1 3D processing
K1 deep learning
K1 remote sensing
K1 GIS
K1 mapping
K1 geospa-tial intelligence
K1 computer vision
K1 machine learning
K1 wide area surveillance
K1 automatic target recognition
K1 scene understanding
K1 classification
K1 transfer learning
SP 1
OP 7
LK http://dx.doi.org/https://doi.org/10.1109/AIPR52630.2021.9762086
DO https://doi.org/10.1109/AIPR52630.2021.9762086
SF ELIB - SuUB Bremen

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