MDFNet: an unsupervised lightweight network for ear print recognition

In this paper, we propose an unsupervised lightweight network with a single layer for ear print recognition. We refer to this method by MDFNet because it relies on gradient Magnitude and Direction alongside with responses of data-driven Filters. At first, we align ear using Convolution Neural Networ...

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Detalles Bibliográficos
Autores principales: Aiadi, Oussama, Khaldi, Belal, Saadeddine, Cheraa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206135/
https://www.ncbi.nlm.nih.gov/pubmed/35757492
http://dx.doi.org/10.1007/s12652-022-04028-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206135/
https://www.ncbi.nlm.nih.gov/pubmed/35757492
http://dx.doi.org/10.1007/s12652-022-04028-z

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