A Survey on Self-Supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang et al.
2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence · 451 citations
Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data can be expensive and time-consuming. Self-supervised learning (SSL), a subset of unsupervised learning, aims to learn discriminative features from unlabeled data without relying on human-annotated labels. SSL has garnered significant attention recently, leading to the development of numerous related algorithms. However, there is a dearth of comprehensive studies that elucidate the connections and evolution of differ…
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