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 |
- 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]
- 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]
- Alex Krizhevsky, Ilya Sutskever, and Geoff Hinton. Imagenet classfication with deep convolutional neural networks. Inadvances in NISP,2012 [Google Scholar]
- 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. [Google Scholar]
- 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]
- 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]
- 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]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.