Image classification systems recently made a giant leap with the advancement of deep
neural networks. However, these systems require an excessive amount of labeled data to be …

Crowdsourcing provides an efficient way to obtain multiple noisy labels from different crowd
workers for each unlabeled instance. Label integration methods are designed to infer the …

Crowdsourcing services provide a fast, efficient, and cost-effective way to obtain large
labeled data for supervised learning. Unfortunately, the quality of crowdsourced labels …

Background. Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic
liver diseases. Machine learning techniques were introduced to evaluate the optimal …

Crowdsourcing makes it much faster and cheaper to obtain labels for a large amount of data
used in supervised learning. In the crowdsourcing scenario, an integrated label is inferred …

In crowdsourcing scenarios, we can hire crowd workers to label crowdsourced tasks and
then use label integration algorithms to infer the integrated label for each instance in the …

Crowdsourcing services provide a fast, efficient, and cost-effective approach to obtaining
labeled data, particularly for human-like tasks. In a crowdsourcing scenario, after ground …

Crowdsourcing system provides an easy way to obtain labeled training data. However, the
labels provided by non-expert labelers often appear low quality. So in practice, each sample …

Crowdsourcing services provide an efficient and relatively inexpensive approach to obtain
substantial amounts of labeled data by employing crowd workers. It is obvious that the …

Crowdsourcing has attracted considerable attention in recent years. A large amount of
labeled data can be obtained efficiently and cheaply from the crowdsourcing platform …