Face illumination processing via dense feature maps and multiple receptive fields-Reference-Cited by-同舟云学术

Face illumination processing via dense feature maps and multiple receptive fields

Published:2021-04-16 Issue:16 Volume:57 Page:627-629
ISSN:0013-5194
Container-title:Electronics Letters
language:en
Short-container-title:Electron. lett.

Author:

Ling Shenggui¹²^ORCID,Fu Keren³^ORCID,Lin Ye¹^ORCID,You Di¹^ORCID,Cheng Peng⁴^ORCID

Affiliation:

1. The National Key Laboratory of Fundamental Science on Synthetic Vision Sichuan University Chengdu Sichuan China

2. Neijiang Vocational&Technical College Neijiang Sichuan China

3. The College of Computer Science Sichuan University Chengdu Sichuan China

4. The School of Aeronautics and Astronautics Sichuan University Chengdu Sichuan China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ell2.12181

Reference29 articles.

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2. Wang M. Deng W.:Deep face recognition: A survey. arXiv:1804.06655 (2018)

3. FER‐Net: facial expression recognition using densely connected convolutional network

4. Gradient-based learning applied to document recognition

5. Krizhevsky I.A. Hinton E.:Imagenet classification with deep convolutional neural networks. In:Conference on Neural Information Processing Systems pp.1097–1105.NeurIPS La Jolla CA(2013)

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