Open Access
Issue
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
Article Number 02021
Number of page(s) 4
Section 3D Images Reconstruction and Virtual System
DOI https://doi.org/10.1051/matecconf/201823202021
Published online 19 November 2018
  1. Rothe R, Timofte R, Gool L V. DEX: Deep EXpectation of Apparent Age from a Single Image[C].IEEE International Conference on Computer Vision Workshop. IEEE, 2016:252-257. [Google Scholar]
  2. Guo G, Fu Y, Dyer C R, et al.. Image-based human age estimation by manifold learning and locally adjusted robust regression.[J]. IEEE Transactions on Image Processing, 2008, 17(7): 1178-1188. [CrossRef] [Google Scholar]
  3. Alex Krizhevsky, Ilya Sutskever, and Geoff Hinton. Imagenet classfication with deep convolutional neural networks. Inadvances in NISP,2012 [Google Scholar]
  4. Zhang K, Zhang Z, Li Z, et al.. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks[J]. IEEE Signal Processing,Letters,2016, 23(10): 1499-1503. [NASA ADS] [CrossRef] [Google Scholar]
  5. Escalera S, Fabian J, Pardo P, et al..ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results[C]. IEEE International Conference on Computer Vision Workshop. IEEE, 2015:243-251. [Google Scholar]
  6. Hu Z, Wen Y, Wang J, et al.. Facial Age Estimation With Age Difference[J]. IEEE Transactions on Image Processing, 2017, 26(7): 3087-3097. [CrossRef] [Google Scholar]
  7. S. Ioffe and C. Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In Proceedings of The 32nd International Conference on Machine Learning, pages 448–456, 2015 [Google Scholar]

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