Richard Comont

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We present an incremental Bayesian model that resolves key issues of crowd size and data quality for consensus labeling. We evaluate our method using data collected from a real-world citizen science program, B<scp>ee</scp>W<scp>atch</scp>, which invites members of the public in the United Kingdom to classify (label) photographs of bumblebees as one of 22(More)
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