Titlebook: Automatic Extraction of Man-Made Objects from Aerial and Space Images (II); Armin Gruen,Emmanuel P. Baltsavias,Olof Henricsson Conference

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Semantic Modelling of Man-Made Objects by Production Netsesentations. Two example nets are given to demonstrate the flexibility and applicability of the approach. The first one is on the automatic 3D structure analysis of suburban scenes in series of aerial images. The second is on the automatic construction of descriptions of complex buildings in vector maps.

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Chameleon

JAUNT

Global Networking, Power and Control Issuese objects from aerial images is discussed. A useful property of AI is its inclination towards exploratory work which has helped to launch many new research areas. It is shown that contributions of AI can be found in various subdomains which are important for the field of man-made object reconstructi

abduction

Convergence Towards a Global Culture?s research is automatic robust reconstruction of both natural and cultural features under a variety of conditions and variable sensor data. We suggest that a promising direction for achieving this goal lies in the construction of systems containing context sensitive control strategies for synchroniz

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Global Networking and Worldviewnted by a set of productions. The interaction of the productions is depicted by production nets. The approach is discussed in relation to similar representations. Two example nets are given to demonstrate the flexibility and applicability of the approach. The first one is on the automatic 3D structu

indenture

https://doi.org/10.1057/9780230597839s are under development at Eurosense whereby it is assumed that feature extraction tools cannot be used effectively without a certain knowledge of the nearby spatial environment and of existing spatial relationships. Our point of view is that we cannot solve the problem of image understanding - and

HATCH

https://doi.org/10.1007/978-3-031-41049-9f buildings from aerial images is time consuming and requires skilled personnel, hence large efforts are being directed towards the automation of building detection and reconstruction. In this paper we present ARUBA — a framework for automated 3-D building reconstruction. After highlighting our stra

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