DETECTION OF PRINTED FALSE ATTACKS USING NEURAL NETWORKS

Абдукадиров, Бахтиёр

Al-Farg'oniy avlodlari · 2025-yil

Annotatsiya

This article discusses a method for detecting false positives against a biometric facial recognition system based on deep convolutional neural networks. The proposed method is designed to detect printed false positives and is tested on open databases of real and fake faces, and the results are analyzed. The types of false positive attacks launched against a biometric system based on existing faces are analyzed.

Maqola ma’lumotlari
MualliflarАбдукадиров, Бахтиёр
JurnalAl-Farg'oniy avlodlari
Nashr sanasi2025-10-03
Son3
Betlar115-118
TilRus

Kalit so‘zlar

биометрическая система, ложная атака, локальный бинарный шаблон, метод опорных векторов, сверточные нейронные сети, рекуррентная сеть, метрики оценки классификatsiи, biometric system, false alarm attack, local binary pattern, support vector machine, convolutional neural networks, recurrent network, classification evaluation metrics, biometrik tizim, soxta hujum, lokal binar shablon, tayanch vektorlar usuli, o‘ramli neyron tarmoqlari, rekurent tarmoq, klassifikatsiyani baholash metrikalari

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