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Effect of Laplacian Smoothing Stochastic Gradient Descent with Angular Margin Softmax Loss on Face Recognition

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Intelligent Technologies and Applications (INTAP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1198))

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Abstract

An important task in deep learning for face recognition is to use proper loss functions and optimization technique. Several loss functions have been proposed using stochastic gradient descent for this task. The main purpose of this work is to propose the strategy to use the Laplacian smoothing stochastic gradient descent with combination of multiplicative angular margin to enhance the performance of angularly discriminative features of angular margin softmax loss for face recognition. The model is trained on a most popular face recognition dataset CASIA-WebFace and it achieves the state-of-the-art performance on several academic benchmark datasets such as Labeled Face in the Wild (LFW), YouTube Faces (YTF), VGGFace1 and VGGFace2. Our method achieves a new record accuracy of 99.54% on LFW dataset. On YTF dataset it achieves 95.53% accuracy.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, People’s Republic of China

    Mansoor Iqbal

  2. Department of Electrical and Computer Engineering, Air University, Islamabad, Pakistan

    Muhammad Awais Rehman

  3. Mathematics Department, Faculty of Science, University of Hail, Hail, Kingdom of Saudi Arabia

    Naveed Iqbal

  4. School of Sciences, Tianjin University TJU, Tianjin, People’s Republic of China

    Zaheer Iqbal

Authors
  1. Mansoor Iqbal
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  2. Muhammad Awais Rehman
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  3. Naveed Iqbal
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  4. Zaheer Iqbal
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Corresponding author

Correspondence to Mansoor Iqbal .

Editor information

Editors and Affiliations

  1. Islamia University of Bahawalpur, Baghdad, Pakistan

    Imran Sarwar Bajwa

  2. Metropolitan University, Belgrade, Serbia

    Tatjana Sibalija

  3. University of Technology Malaysia, Johor Bahru, Malaysia

    Dayang Norhayati Abang Jawawi

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Iqbal, M., Rehman, M.A., Iqbal, N., Iqbal, Z. (2020). Effect of Laplacian Smoothing Stochastic Gradient Descent with Angular Margin Softmax Loss on Face Recognition. In: Bajwa, I., Sibalija, T., Jawawi, D. (eds) Intelligent Technologies and Applications. INTAP 2019. Communications in Computer and Information Science, vol 1198. Springer, Singapore. https://doi.org/10.1007/978-981-15-5232-8_47

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  • DOI: https://doi.org/10.1007/978-981-15-5232-8_47

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5231-1

  • Online ISBN: 978-981-15-5232-8

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