Face Verification and Forgery Detection for Ophthalmic Surgery Images

Although modern face verification systems are accessible and accurate, they are not always robust to pose variance and occlusions. Moreover, accurate models require a large amount of data to train. We structure our experiments to operate on small amounts of data obtained from an NGO that funds ophth...

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Veröffentlicht in:	arXiv.org 2018-11
Hauptverfasser:	Kaushal Bhogale, Shankar, Nishant, Juvekar, Adheesh, Padhi, Asutosh
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Error analysis Face recognition Forgery Image detection Inference Model accuracy Model testing Surgery
Online-Zugang:	Volltext
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