Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.
Markus Bauer,
Christoph Augenstein
Abstract:Artificial Intelligence (AI) represents a highly investigated area of study at present and has already become an indispensable component within an extensive range of business models and applications. One major downside of current supervised AI approaches lies in the need of numerous annotated data points to train the models. Self-supervised learning (SSL) circumvents the need for annotation, by creating supervision signals such as labels from the data itself, rather than requiring experts for this task. Curren… Show more
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