Processing Collections of Geo-Referenced Images for Natural Disasters

Mostrar todas las versiones(2)

After disaster strikes, emergency response teams need to work fast. In this context, crowdsourcing has emerged as a powerful mechanism where volunteers can help to process different tasks such as processing complex images using labeling and classification techniques. In this work we propose to addre...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Loor, Fernando, Gil-Costa, Verónica, Marín, Mauricio
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2018
Materias:
Ciencias Informáticas
geo-referenced images, support platforms for natural disaster, P2P network
sistemas de información geográfica
prevención de desastres
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/70000
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-70000
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
geo-referenced images, support platforms for natural disaster, P2P network
sistemas de información geográfica
prevención de desastres
spellingShingle Ciencias Informáticas
geo-referenced images, support platforms for natural disaster, P2P network
sistemas de información geográfica
prevención de desastres
Loor, Fernando
Gil-Costa, Verónica
Marín, Mauricio
Processing Collections of Geo-Referenced Images for Natural Disasters
topic_facet Ciencias Informáticas
geo-referenced images, support platforms for natural disaster, P2P network
sistemas de información geográfica
prevención de desastres
description After disaster strikes, emergency response teams need to work fast. In this context, crowdsourcing has emerged as a powerful mechanism where volunteers can help to process different tasks such as processing complex images using labeling and classification techniques. In this work we propose to address the problem of how to efficiently process large volumes of georeferenced images using crowdsourcing in the context of high risk such as natural disasters. Research on citizen science and crowdsourcing indicates that volunteers should be able to contribute in a useful way with a limited time to a project, supported by the results of usability studies. We present the design of a platform for real-time processing of georeferenced images. In particular, we focus on the interaction between the crowdsourcing and the volunteers connected to a P2P network.
format Objeto de conferencia
Objeto de conferencia
author Loor, Fernando
Gil-Costa, Verónica
Marín, Mauricio
author_facet Loor, Fernando
Gil-Costa, Verónica
Marín, Mauricio
author_sort Loor, Fernando
title Processing Collections of Geo-Referenced Images for Natural Disasters
title_short Processing Collections of Geo-Referenced Images for Natural Disasters
title_full Processing Collections of Geo-Referenced Images for Natural Disasters
title_fullStr Processing Collections of Geo-Referenced Images for Natural Disasters
title_full_unstemmed Processing Collections of Geo-Referenced Images for Natural Disasters
title_sort processing collections of geo-referenced images for natural disasters
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/70000
work_keys_str_mv AT loorfernando processingcollectionsofgeoreferencedimagesfornaturaldisasters
AT gilcostaveronica processingcollectionsofgeoreferencedimagesfornaturaldisasters
AT marinmauricio processingcollectionsofgeoreferencedimagesfornaturaldisasters
bdutipo_str Repositorios
_version_ 1764820481979973633

Ejemplares similares