Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning

A. Vetrivel, N. Kerle, M. Gerke, F.C. Nex, G. Vosselman

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Original languageEnglish
Title of host publicationProceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands
EditorsN. Kerle, M. Gerke, S. Lefevre
Place of PublicationEnschede
PublisherUniversity of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
Pages1-5
Number of pages5
ISBN (Print)978-90-365-4201-2
DOIs
Publication statusPublished - 14 Sep 2016
Event6th International Conference on Geographic Object-Based Image Analysis 2016: Solutions & Synergies - Enschede, Enschede, Netherlands
Duration: 14 Sep 201616 Sep 2016
https://www.geobia2016.com/

Conference

Conference6th International Conference on Geographic Object-Based Image Analysis 2016
Abbreviated titleGEOBIA 2016
CountryNetherlands
CityEnschede
Period14/09/1616/09/16
Internet address

Keywords

  • METIS-321196

Cite this

Vetrivel, A., Kerle, N., Gerke, M., Nex, F. C., & Vosselman, G. (2016). Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning. In N. Kerle, M. Gerke, & S. Lefevre (Eds.), Proceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands (pp. 1-5). Enschede: University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC). https://doi.org/10.3990/2.369