Through the Citizen Scientists’ Eyes: Insights into Using Citizen Science with Machine Learning for Effective Identification of Unknown-Unknowns in Big Data

Through the Citizen Scientists’ Eyes: Insights into Using Citizen Science with Machine Learning for Effective Identification of Unknown-Unknowns in Big Data

In the era of rapidly growing astronomical data, the gap between data collection and analysis is a significant barrier, especially for teams searching for rare scientific objects. Although machine learning (ML) can quickly parse large data sets, it struggles to robustly identify scientifically inter...

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Bibliographic Details
Main Authors: Kameswara Bharadwaj Mantha, Hayley Roberts, Lucy Fortson, Chris Lintott, Hugh Dickinson, William Keel, Ramanakumar Sankar, Coleman Krawczyk, Brooke Simmons, Mike Walmsley, Izzy Garland, Jason Shingirai Makechemu, Laura Trouille, Clifford Johnson
Format: Article
Language:English
Published: Ubiquity Press 2024-12-01
Series:Citizen Science: Theory and Practice
Subjects:
deep learning
anomaly detection
human-machine optimization
unsupervised learning
astronomy imaging
Online Access:https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/740
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https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/740

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