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, Türkiyefatih.firstname.lastname@example.org, email@example.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!