A comparison among keyframe extraction techniques for CNN classification based on video periocular images-Reference-Cited by-同舟云学术

A comparison among keyframe extraction techniques for CNN classification based on video periocular images

Published:2021-01-13 Issue:8 Volume:80 Page:12843-12856
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Toledo Ferraz Carolina^ORCID,Barcellos William,Pereira Junior Osmando,Trevisan Negri Borges Tamiris,Garcia Manzato Marcelo,Gonzaga Adilson,Hiroki Saito José

Funder

Nvidia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-020-10384-9.pdf

Reference45 articles.

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3. Ambika DR, Radhika KR, Seshachalam D (2012) The eye says it all: Periocular region methodologies. In: 2012 International conference on multimedia computing and systems, pp 180–185

4. Angiulli F, Astorino A (2010) Scaling up support vector machines using nearest neighbor condensation. IEEE Trans Neural Netw 21(2):351–357

5. Balcázar J, Dai Y, Watanabe O (2001) A random sampling technique for training support vector machines. In: Abe N, Khardon R, Zeugmann T (eds) Algorithmic learning theory. Springer, Berlin, pp 119–134

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