Apr 15, 2024 · In this tutorial, we will survey and synthesize a wide spectrum of existing studies on crowdsourced data management.

Jun 16, 2024 · Besides the re- balancing effects discussed in the previous sections, this approach allows scaling up to large pools any. AL strategies and models without ...

Feb 20, 2024 · Therefore, crowd- sourcing has been widely adopted to alleviate the cost of col- lecting labels, which also inevitably introduces label noise and eventually ...

Jan 15, 2024 · Combining human and machine intelligence in large-scale crowdsourcing. ... Scaling up crowd-sourcing to very large datasets: A case for active learning.

Feb 2, 2024 · Dr. Gianluca Demartini is an Associate Professor in Data Science at the University of Queensland, School of Electrical Engineering and Computer Science.

Jul 28, 2024 · This blog discusses the main challenges and limitations of active learning, a machine learning technique that selects the most informative data for labeling ...

Aug 8, 2024 · In this paper, we present a new method for screening people relying on metacognition and aggregation of votes with confidence and measuring their performance.

Jun 19, 2024 · This paper provides a review of the state-of-the-art methods in data collection, data labeling, and the improvement of existing data and models.

Oct 30, 2023 · This project is a case study, where we worked with a domain expert to create a model which could segment teeth in dental x-rays.

Apr 25, 2024 · In this work, we integrate many such factors into a simulation model of crowdworker behaviour rooted in the theory of computational rationality.