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A General Framework for Human-Machine Digitization of Geogr..:

, In: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems,

Michael, Chris J. ; Dennis, Steven M. ; Maryan, Corey.. - p. 259-268 , 2019

Link: https://dl.acm.org/doi/10.1145/3347146.3359370

RT 
T1 <cTitle>Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems</cTitle>: T1 <Title>A General Framework for Human-Machine Digitization of Geographic Regions from Remotely Sensed Imagery</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3359370&Exemplar=1&LAN=DE
				
A1 Michael, Chris J.
A1 Dennis, Steven M.
A1 Maryan, Corey
A1 Irving, Samuel
A1 Palmsten, Margaret L.
PB ACM
YR 2019
K1 geographic region digitization
K1 human-centered machine learning
K1 human-machine teams
K1 Information systems
K1 Information systems applications
K1 Spatial-temporal systems
K1 Geographic information systems
K1 Computing methodologies
K1 Machine learning
K1 Learning settings
K1 Active learning settings
K1 Online learning settings
K1 Artificial intelligence
K1 Computer vision
K1 Computer vision problems
K1 Interest point and salient region detections
SP 259
OP 268
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3347146.3359370
DO https://dl.acm.org/doi/10.1145/3347146.3359370
SF ELIB - SuUB Bremen

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