TY  - JOUR
ID  - iiasa13833
UR  - http://ceur-ws.org/Vol-1662/
A1  - Nurmukhametov, O.R.
A1  - Baklanov, A.
Y1  - 2016///
N2  - 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.
PB  - CEUR Workshop Proceedings
JF  - Modern Problems in Mathematics and its Applications
VL  - 1662
KW  - Crowdsourcing; Data quality; Geo-Wiki; Image classification
SN  - 1613-0073
TI  - A method for increasing the accuracy of image annotating in crowd-sourcing
SP  - 206
AV  - public
EP  - 214
ER  -