Wet and Fine-Grained

Fingerprint recognition is crucial for device and data

security, especially with the widespread use of capacitive sensors

in mobile devices. However, denoising wet fingerprints from

these sensors poses challenges due to small fingerprint areas,

limited features, and significant moisture-induced dark regions.

Our ”DRB-FD” method combines a Featured Discriminator (FD)

and a Deformed Residual Block (DRB) with attention mechanisms,

drop-out layers, and pre-activation. In experiments using the Nasic9395

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