eprintid: 13833
rev_number: 9
eprint_status: archive
userid: 353
dir: disk0/00/01/38/33
datestamp: 2016-09-26 11:42:12
lastmod: 2021-08-27 17:27:48
status_changed: 2016-09-26 11:42:12
type: article
metadata_visibility: show
creators_name: Nurmukhametov, O.R.
creators_name: Baklanov, A.
creators_id: 2067
creators_orcid: 0000-0003-1599-3618
title: A method for increasing the accuracy of image annotating in crowd-sourcing
ispublished: pub
divisions: prog_asa
keywords: Crowdsourcing; Data quality; Geo-Wiki; Image classification
abstract: Crowdsourcing is a new approach to solve tasks when a group of volunteers replaces experts. Recent results show that crowdsourcing is an efficient tool for annotating large datasets. Geo-Wiki is an example of successful citizen science projects. The goal of Geo-Wiki project is to improve a global land cover map by applying crowdsourcing for image recognition. In our research, we investigate methods for increasing reliability of data collected during The Cropland Capture Game (Geo-Wiki). In this regard, we performed analysis of all main steps of the crowdsourcing campaign: image processing and aggregation of collected votes. During the research, we used methods of Computer Vision and Machine Learning. This allowed us to increase accuracy of the aggregated votes from 76% to 87%. Copyright © by the paper's authors.
date: 2016
date_type: published
publisher: CEUR Workshop Proceedings
official_url: http://ceur-ws.org/Vol-1662/
creators_browse_id: 22
full_text_status: public
publication: Modern Problems in Mathematics and its Applications
volume: 1662
pagerange: 206-214
refereed: TRUE
issn: 1613-0073
coversheets_dirty: FALSE
fp7_project: no
fp7_type: info:eu-repo/semantics/article
citation:   Nurmukhametov, O.R. & Baklanov, A. <https://pure.iiasa.ac.at/view/iiasa/22.html> ORCID: https://orcid.org/0000-0003-1599-3618 <https://orcid.org/0000-0003-1599-3618>  (2016).  A method for increasing the accuracy of image annotating in crowd-sourcing.   Modern Problems in Mathematics and its Applications 1662 206-214.       
document_url: https://pure.iiasa.ac.at/id/eprint/13833/1/A%20method%20for%20increasing%20the%20accuracy%20of%20image%20annotating%20in%20crowd-sourcing.pdf