https://pure.iiasa.ac.at/id/eprint/13833 2021-08-27T17:27:48Z info:eu-repo/semantics/descriptiveMetadata https://pure.iiasa.ac.at/id/eprint/13833/ A method for increasing the accuracy of image annotating in crowd-sourcing Nurmukhametov, O.R. Baklanov, A. 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. CEUR Workshop Proceedings 2016 Article PeerReviewed text en cc_by https://pure.iiasa.ac.at/id/eprint/13833/1/A%20method%20for%20increasing%20the%20accuracy%20of%20image%20annotating%20in%20crowd-sourcing.pdf 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. http://ceur-ws.org/Vol-1662/ info:eu-repo/semantics/objectFile info:eu-repo/semantics/humanStartPage