Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image

Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image

Our research is fingerprint reconstruction based on a convolutional autoencoder. We combine the perceptual measurement as a multi-loss function to give satisfactory weight correction, such as the structural similarity index measure (SSIM), Mean Absolute Error (MAE), and peak signal-to-noise rat...

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Bibliographic Details
Main Authors: Raswa, Farchan Hakim, Halberd, Franki, Harjoko, Agus, Wahyono, Wahyono, Lee, Chung-Ting, Wang, Jia Ching
Format: Other
Language:English
Published: Proceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022 2022
Subjects:
Information and Computing Sciences
Online Access:https://repository.ugm.ac.id/284285/1/169.Multi-loss_Function_in_Robust_Convolutional_Autoencoder_for_Reconstruction_Low-quality_Fingerprint_Image.pdf

Internet

https://repository.ugm.ac.id/284285/1/169.Multi-loss_Function_in_Robust_Convolutional_Autoencoder_for_Reconstruction_Low-quality_Fingerprint_Image.pdf

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