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Learning a Fixed-Length Fingerprint Representation
[article]
2019
arXiv
pre-print
We present DeepPrint, a deep network, which learns to extract fixed-length fingerprint representations of only 200 bytes. DeepPrint incorporates fingerprint domain knowledge, including alignment and minutiae detection, into the deep network architecture to maximize the discriminative power of its representation. The compact, DeepPrint representation has several advantages over the prevailing variable length minutiae representation which (i) requires computationally expensive graph matching
arXiv:1909.09901v2
fatcat:e5bitszt7jeopjrlpzr5nhtbee