OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Overview of the ImageCLEF 2017 Population Estimation (Remote) Task

Arenas, Helbert and Islam, Md Bayzidul and Mothe, Josiane Overview of the ImageCLEF 2017 Population Estimation (Remote) Task. (2017) In: International Conference of the CLEF Association, CLEF 2017 Labs Working Notes (CLEF 2017)), 11 September 2017 - 14 September 2017 (Dublin, Ireland).

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
241kB

Official URL: http://ceur-ws.org/Vol-1866/invited_paper_2.pdf

Abstract

Estimating population has many applications as planning disaster responses, communication infrastructure, or development activities. In 2017, ImageCLEF Lab introduced a new pilot task: the Population Estimation (or Remote) task which aims at estimating the population of an area of interest by exploring Copernicus earth observation data (i.e. free Sentinel-2 satellite images). In line with the goal of FabSpace 2.0 project, a European Unions initiative to bring Geo-Enthusiast together around the 6 European universities in collaboration with Business Incubation Centers, participated to this challenge. This paper presents the results that were obtained by the participants as well as a brief summary of some of the approaches that were used.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-01912784
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Technische Universität Darmstadt (GERMANY)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Funders:
European Unions Horizon 2020 Research - Innovation programme under the Grant Agreement n693210
Statistics:download
Deposited By: IRIT IRIT
Deposited On:19 Sep 2018 14:21

Repository Staff Only: item control page