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Semantic Information Extraction from UAV Imagery and Aerial Imagery

open access: yes, 2019
A central theme in the field of photogrammetry is the improvement of geo-spatial accuracy. However, the accurate geo-localization for low-lost UAV systems that are equipped with cheap and light GNSS/INS remains an open problem. In contrast, aerial imagery acquired by manned aircrafts usually has much higher geo-referencing accuracy of up to centimeter
openaire   +2 more sources

Gran canaria vegetation segmentation dataset from multi-year aerial imagery for environmental monitoring and conservation. [PDF]

open access: yesData Brief
Salas-Cáceres J   +4 more
europepmc   +1 more source

Efficient geospatial mapping of buildings, woodlands, water and roads from aerial imagery using deep learning. [PDF]

open access: yesPeerJ Comput Sci
Abbas S   +6 more
europepmc   +1 more source

Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys. [PDF]

open access: yesPLoS One
Ke TW   +9 more
europepmc   +1 more source

Exploring agricultural landscape change from the second half of the twentieth century onwards: combining aerial imagery with farmer perspectives. [PDF]

open access: yesLandsc Ecol
Mohr F   +8 more
europepmc   +1 more source

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