Facial Recognition Via Transfer Learning: Fine-Tuning Keras_vggface
Document Type
Conference Proceeding
Publication Date
12-4-2018
School
Computing Sciences and Computer Engineering
Abstract
© 2017 IEEE. The challenge of developing facial recognition systems has been the focus of many research efforts in recent years and has numerous applications in areas such as security, entertainment, and biometrics. Recently, most progress in this field has come from training very deep neural networks on massive datasets. Here, we use a pre-trained face recognition model and perform transfer learning to produce a network that is capable of making accurate predictions on a much smaller dataset. We also compare our results with results produced by a selection of classical algorithms on the same dataset.
Publication Title
Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
First Page
576
Last Page
579
Recommended Citation
Luttrell, J. B.,
Zhou, Z.,
Zhang, C.,
Gong, P.,
Zhang, Y.
(2018). Facial Recognition Via Transfer Learning: Fine-Tuning Keras_vggface. Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, 576-579.
Available at: https://aquila.usm.edu/fac_pubs/17920