Noise correction of image labeling in crowdsourcing


We investigate the methods of improving data quality, in terms of label accuracy, in the context of image labeling in crowdsourcing. First, we look at three consensus methods for inferring a ground-truth label from the multiple noisy labels obtained from crowdsourcing, i.e., Majority Voting (MV), Dawid Skene (DS), and KOS. We then apply three noise… (More)
DOI: 10.1109/ICIP.2015.7351042


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