Cited by 9Face recognition and analysisFace and Expression RecognitionBiometric Identification and Security

A Comparative Study Between Deep Learning and Traditional Machine Learning Techniques for Facial Biometric Recognition

Finizola, Jonnathann Silva, Targino, Jonas Mendonça, Teodoro, Felipe Gustavo Silva, de Moraes Lima, Clodoaldo Aparecido·2018·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-030-03928-8_18

Cites

19 of 19 references verified0 citation errors · 0 not checkable

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  • When the data size is large, deep learning algorithms outperform traditional machine learning algorithms.

    “When the data size is large, several studies [11-14] have shown that DL algorithms outperform the traditional ML algorithms.”

    From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [13]

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Authors
Finizola, J. S., Targino, J. M., Teodoro, F. G. S., & de Moraes Lima, C. A.
Affiliations
Universidade de São Paulo (BR)
Corresponding author
  • Finizola, Jonnathann Silva
  • Targino, Jonas Mendonça
  • Teodoro, Felipe Gustavo Silva
Venue
Lecture Notes in Computer Science
Published
2018
Pages
217-228
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2899781844
Cited by
9
References
20
Citations by year
2024: 1 · 2023: 2 · 2021: 4 · 2020: 1 · 2019: 1
FWCI
0.45
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
  • Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
Keywords
face recognition, face biometrics, convolutional neural networks, traditional machine learning, k-nearest neighbors, support vector machine, extreme learning machine, artificial neural networks, optimum-path forest, biometric identification, algorithm comparison

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