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Consequential Advancements of Self-Supervised Learning (SSL) in Deep Learning Contexts

Self-supervised learning (SSL) is a potential deep learning (DL) technique that uses massive volumes of unlabeled data to train neural networks. SSL techniques have evolved in response to the poor classification performance of conventional and even modern machine learning (ML) and DL models of enorm...

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I tiakina i:
Ngā kaituhi matua: Mohammed Majid Abdulrazzaq, Nehad T. A. Ramaha, Alaa Ali Hameed, Mohammad Salman, Dong Keon Yon, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee
Hōputu: Artigo
Reo:Inglês
I whakaputaina: MDPI AG 2024-03-01
Rangatū:Mathematics
Ngā marau:
deep learning (DL)
self-supervised learning (SSL)
machine learning (ML)
cognition
classification
data annotation
Urunga tuihono:https://www.mdpi.com/2227-7390/12/5/758
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