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
Vetrivel, A. ; Kerle, N. ; Gerke, M. ; Nex, F.C. ; Vosselman, G. / Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning. Proceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands. editor / N. Kerle ; M. Gerke ; S. Lefevre. Enschede : University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), 2016. pp. 1-5
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title = "Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning",
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author = "A. Vetrivel and N. Kerle and M. Gerke and F.C. Nex and G. Vosselman",
year = "2016",
month = "9",
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language = "English",
isbn = "978-90-365-4201-2",
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booktitle = "Proceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands",
publisher = "University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)",

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Vetrivel, A, Kerle, N, Gerke, M, Nex, FC & 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. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), Enschede, pp. 1-5, 6th International Conference on Geographic Object-Based Image Analysis 2016, Enschede, Netherlands, 14/09/16. https://doi.org/10.3990/2.369

Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning. / Vetrivel, A.; Kerle, N.; Gerke, M.; Nex, F.C.; Vosselman, G.

Proceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands. ed. / N. Kerle; M. Gerke; S. Lefevre. Enschede : University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), 2016. p. 1-5.

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

TY - GEN

T1 - Towards automated satellite image segmentation and classification for assessing disaster damage using data-specific features with incremental learning

AU - Vetrivel, A.

AU - Kerle, N.

AU - Gerke, M.

AU - Nex, F.C.

AU - Vosselman, G.

PY - 2016/9/14

Y1 - 2016/9/14

KW - METIS-321196

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2016/conf/vetrivel_tow.pdf

U2 - 10.3990/2.369

DO - 10.3990/2.369

M3 - Conference contribution

SN - 978-90-365-4201-2

SP - 1

EP - 5

BT - Proceedings of GEOBIA 2016 : Solutions and synergies, 14-16 September 2016, Enschede, Netherlands

A2 - Kerle, N.

A2 - Gerke, M.

A2 - Lefevre, S.

PB - University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)

CY - Enschede

ER -

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