13833 10 71221 2 197390 document 71221 A method for increasing the accuracy of image annotating in crowd-sourcing.pdf application/pdf c213050ca497a88e0476c459fe8fd2c6 MD5 3559700 2016-09-26 06:51:05 https://pure.iiasa.ac.at/id/eprint/13833/1/A%20method%20for%20increasing%20the%20accuracy%20of%20image%20annotating%20in%20crowd-sourcing.pdf 13833 1 1 application/pdf text In Russian en public cc_by

A method for increasing the accuracy of image annotating in crowd-sourcing.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/71221 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/71221 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/71221 archive 353 disk0/00/01/38/33 2016-09-26 11:42:12 2024-01-04 14:04:35 2016-09-26 11:42:12 article show Nurmukhametov O.R. Baklanov A. 2067 0000-0003-1599-3618 pub prog_asa Crowdsourcing; Data quality; Geo-Wiki; Image classification 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. 2016 published CEUR Workshop Proceedings http://ceur-ws.org/Vol-1662/ 22 public Modern Problems in Mathematics and its Applications 1662 206-214 TRUE 1613-0073 Geo-Wiki FALSE no info:eu-repo/semantics/article