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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