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Deep Residual Autoencoder for Blind Universal JPEG Restoration

We propose a deep residual autoencoder exploiting Residual-in-Residual Dense Blocks (RRDB) leveraging both the learning capacity of deep residual networks and prior knowledge of the JPEG compression pipeline. The proposed method is blind and universal, consisting of a unique model that effectively r...

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I tiakina i:
Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua: Simone Zini, Simone Bianco, Raimondo Schettini
Hōputu: Artigo
Reo:Inglês
I whakaputaina: IEEE 2020-01-01
Rangatū:IEEE Access
Ngā marau:
Urunga tuihono:https://ieeexplore.ieee.org/document/9050792/
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