Fatih Kahraman1, Cengiz Hüroğlu1, Mümin
İmamoğlu1, Büşra Y. Özcan1,
Muhammed İ. Kalkan1, Muhammet A. Hocaoğlu1,
Ergin Öztürk1, Binnur Kurt2
1TÜBİTAK BİLGEM BTE, Kocaeli, Türkiye
2Omega Eğitim ve Danışmanlık, İstanbul,
Türkiye
fatih.kahraman@tubitak.gov.tr, binnur.kurt@gmail.com
Anahtar Kelimeler — Kitle Kaynak, Görüntü
Kıymetlendirme, Uzaktan Algılama.
Abstract— Although
today’s computing systems present powerful solutions to process big data with
the help of recent advances in cloud computing technologies, many problems
remain unsolved due to lack of acceptable algorithms. For instance, searching
for a lost plane or damage assessment after earthquake on a high-resolution
remote sensing satellite image are unsolved problems. In recent years, in order
to solve such unsolved problems, a group of expert and non-expert people called
crowd is utilized. An expert in the group is not expected to solve the original
problem. Instead, geo-spatial image is partitioned in space and each expert in
the pool studies the partition assigned to him/her. The solution to the
original problem is obtained by merging the partial solutions. There are two
open issues: i) How to partition the space and how to distribute the partitions
to the crowd ii) How to merge the partial solutions. In this study, we device
several algorithms to address these issues and introduce our web-based platform and crowd-sourcing
implementation.
Keywords — Crowdsourcing, Image Exploitation,
Remote Sensing.
Bu çalışmamız 17 Mayıs 2015 tarihinde IEEE 23. Sinyal İşleme ve İletişim Uygulamaları Kurultayında sunulacaktır!
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