Abstract
The three main challenging problems in face recognition, i.e., recognizing a face with different expressions, recognizing a face under different lighting conditions, and recognizing a face in different poses are considered here. In recent years, Convolutional Neural Network (CNN) has been widely applied to face recognition problem because of its good performance. The application of CNN architectures for the above three challenging problems is discussed in this chapter.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Bhat, F.A., Wani, M.A.: Performance comparison of major classical face recognition techniques. In: 2014 13th International Conference on Machine Learning and Applications (ICMLA), IEEE (2014)
Bhat, F.A., Wani, M.A.: Face recognition using convolutional neural network. In: 2017 4th International Conference on Computing for Sustainable Global Development (INDIACom), pp. 460–464, IEEE (2017)
Bhat, F.A., Wani, M.A.: A robust face recognition model based on convolutional neural networks. J. Artif. Intell. Res. Adv. 5(1), 1–11 (2018)
Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. BMVC 1(3) (2015)
Sun, Y., Wang, X., Tang, X.: Deep learning face representation from predicting 10,000 classes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2014a)
Sun, Y., et al.: Deep learning face representation by joint identification-verification. In: Advances in Neural Information Processing Systems (2014b)
Sun, Y., Wang, X., Tang, X.: Deeply learned face representations are sparse, selective, and robust. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2015)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Wani, M.A., Bhat, F.A., Afzal, S., Khan, A.I. (2020). Supervised Deep Learning in Face Recognition. In: Advances in Deep Learning. Studies in Big Data, vol 57. Springer, Singapore. https://doi.org/10.1007/978-981-13-6794-6_6
Download citation
DOI: https://doi.org/10.1007/978-981-13-6794-6_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6793-9
Online ISBN: 978-981-13-6794-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)