SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS

SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS

This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recen...

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Bibliographic Details
Main Authors:	D. Marmanis, J. D. Wegner, S. Galliani, K. Schindler, M. Datcu, U. Stilla
Format:	Article
Language:	English
Published:	Copernicus Publications 2016-06-01
Series:	ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:	http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-3/473/2016/isprs-annals-III-3-473-2016.pdf

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