Minimalistic CNN-based ensemble model for gender prediction from face images

Pattern Recognition Letters

Volumn 70, Issue , 2016, Pages 59-65

  Antipov, Grigory ^a,b   Berrani, Sid Ahmed ^a   Dugelay, Jean Luc ^b  

^a ORANGE LABS   (France)

^b EURECOM   (France)

Author keywords

Convolutional neural networks; Gender recognition from face images; Neural networks optimization

Indexed keywords

CONVOLUTION; NEURAL NETWORKS; SOCIAL SCIENCES;

CONVOLUTIONAL NEURAL NETWORK; ENSEMBLE MODELING; FACE IMAGES; GENDER PREDICTIONS; GENDER RECOGNITION; MEMORY REQUIREMENTS; STATE OF THE ART; STATE-OF-THE-ART PERFORMANCE;

FACE RECOGNITION;

EID: 84961155890     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2015.11.011     Document Type: Article

References (34)

1. G. Antipov, S.-A. Berrani, N. Ruchaud, and J.-L. Dugelay Learned vs. hand-crafted features for pedestrian gender recognition Proceedings of the Conference on Multimedia 2015 ACM Brisbane, Australia
2. S. Baluja, and H.A. Rowley Boosting sex identification performance Int. J. Comput. Vis. 71 1 2007 111 119
3. F. Bastien, P. Lamblin, R. Pascanu, J. Bergstra, I. Goodfellow, A. Bergeron, N. Bouchard, D. Warde-Farley, and Y. Bengio Theano: new features and speed improvements CoRR abs/1211.5590 2012
4. J. Bekios-Calfa, J.M. Buenaposada, and L. Baumela Robust gender recognition by exploiting facial attributes dependencies Pattern Recognit. Lett. 36 2014 228 234
5. J. Flora, D. Lochtefeld, D. Bruening, and K. Iftekharuddin Improved gender classification using nonpathological gait kinematics in full-motion video IEEE Trans. Human-Mach. Syst. 45 3 2015 304 314
6. B.A. Golomb, D.T. Lawrence, and T.J. Sejnowski Sexnet: a neural network identifies sex from human faces. Proceedings of the conference on Advances in Neural Information Processing Systems 1990 Denver, USA
7. Y. Gong, L. Liu, M. Yang, and L. Bourdev Compressing deep convolutional networks using vector quantization CoRR 2014 arXiv:org/abs/1412.6115
8. I.J. Goodfellow, Y. Bulatov, J. Ibarz, S. Arnoud, and V. Shet Multi-digit number recognition from street view imagery using deep convolutional neural networks CoRR 2013 arXiv:org/abs/1312.6082
9. K. He, and J. Sun Convolutional neural networks at constrained time cost CoRR 2014 arXiv:org/abs/1412.1710
10. G.B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments Technical Report 2007 University of Massachusetts Amherst
11. S. Jia, and N. Cristianini Learning to classify gender from four million images Pattern Recognit. Lett. 58 2015 35 41
12. A. Krizhevsky, I. Sutskever, and G.E. Hinton Imagenet classification with deep convolutional neural networks Proceedings of the conference on Advances in Neural Information Processing Systems 2012 Lake Tahoe, USA
13. Y. LeCun, and Y. Bengio Convolutional networks for images, speech, and time series The Handbook of Brain Theory and Neural Networks 1998 MIT Press Cambridge MA, USA 255 258
14. G. Levi, and T. Hassner Age and gender classification using convolutional neural networks Proceedings of the Workshop on Analysis and Modeling of Faces and Gestures at CVPR 2015 IEEE Boston, USA
15. B. Li, X.-C. Lian, and B.-L. Lu Gender classification by combining clothing, hair and facial component classifiers Neurocomputing 76 1 2012 18 27
16. J. Lu, G. Wang, and P. Moulin Human identity and gender recognition from gait sequences with arbitrary walking directions IEEE Trans. Inf. Forens. Secur. 9 1 2014 51 61
17. F. Metze, J. Ajmera, R. Englert, U. Bub, F. Burkhardt, J. Stegmann, C. Muller, R. Huber, B. Andrassy, J.G. Bauer, and et al. Comparison of four approaches to age and gender recognition for telephone applications Proceedings of the International Conference on Acoustics, Speech and Signal Processing 2007 IEEE Las-Vegas, USA
18. B. Moghaddam, and M.-H. Yang Learning gender with support faces IEEE Trans. Pattern Anal. Mach. Intell. 24 5 2002 707 711
19. Y. Nesterov A method of solving a convex programming problem with convergence rate o (1/k2) Sov. Math. Dokl. 27 2 1983 372 376
20. P.J. Phillips, H. Wechsler, J. Huang, and P.J. Rauss The Feret database and evaluation procedure for face-recognition algorithms J. Image Vis. Comput. 16 5 1998 295 306
21. A.S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson Cnn features off-the-shelf: an astounding baseline for recognition Proceedings of Computer Vision and Pattern Recognition Workshops 2014 IEEE 512 519
22. O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, and et al. Imagenet large scale visual recognition challenge Int. J. Comput. Vis. 115 3 2015 211 252
23. C. Shan Learning local binary patterns for gender classification on real-world face images Pattern Recognit. Lett. 33 4 2012 431 437
24. H.-C. Shih Robust gender classification using a precise patch histogram Pattern Recognit. 46 2 2013 519 528
25. K. Simonyan, and A. Zisserman Very deep convolutional networks for large-scale image recognition CoRR 2014 arXiv.org/abs/1409.1556
26. N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov Dropout: a simple way to prevent neural networks from overfitting J. Mach. Learn. Res. 15 1 2014 1929 1958
27. Y. Taigman, M. Yang, M. Ranzato, and L. Wolf Deepface: closing the gap to human-level performance in face verification Proceedings of the Conference on Computer Vision and Pattern Recognition 2014 IEEE Columbus, USA
28. J.E. Tapia, and C.A. Perez Gender classification based on fusion of different spatial scale features selected by mutual information from histogram of lbp, intensity, and shape IEEE Trans. Inf. Forens. Secur. 8 3 2013 488 499
29. I. Ullah, M. Hussain, G. Muhammad, H. Aboalsamh, G. Bebis, and A.M. Mirza Gender recognition from face images with local WLD descriptor Proceedings of the International Conference on Systems, Signals and Image Processing 2012 IEEE Vienna, Austria
30. O. Vinyals, A. Toshev, S. Bengio, and D. Erhan Show and tell: a neural image caption generator CoRR 2014 arXiv.org/abs/1411.4555
31. P. Viola, and M. Jones Rapid object detection using a boosted cascade of simple features Proceedings of the Conference on Computer Vision and Pattern Recognition 2001 IEEE Kauai, USA
32. D. Yi, Z. Lei, S. Liao, and S.Z. Li Learning face representation from scratch CoRR 2014 arXiv.org/abs/1411.7923
33. Y. Zeng, X. Xu, Y. Fang, and K. Zhao Traffic sign recognition using extreme learning classifier with deep convolutional features Proceedings of the International Conference on Intelligence Science and Big Data Engineering (IScIDE 2015), Suzhou, China 2015
34. Y. Zhang, Y. Dang, and H. Chen Gender classification for web forums IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 41 4 2011 668 677