Training hierarchical feed-forward visual recognition models using transfer learning from Pseudo-tasks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5304 LNCS, Issue PART 3, 2008, Pages 69-82

  Ahmed, Amr ^a   Yu, Kai ^b   Xu, Wei ^b   Gong, Yihong ^b   Xing, Eric ^a  

^a Carnegie Mellon University

^b NEC LABORATORIES AMERICA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; CONVOLUTIONAL NEURAL NETWORKS; OBJECT RECOGNITION; PATTERN MATCHING; TRANSFER LEARNING;

DIFFERENT DOMAINS; FEATURE LEARNING; FUNCTIONAL BEHAVIORS; GENDER RECOGNITION; NETWORK TRAINING; PRIOR KNOWLEDGE; TRAINING EXAMPLE; VISUAL RECOGNITION;

LEARNING SYSTEMS;

EID: 56749159833     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88690-7_6     Document Type: Conference Paper

References (23)

1. Abu-Mostafa, Y.: Learning from hints in neural networks. Journal of Complexity 6, 192-198 (1990)
2. Ando, R., Zhang, T.: A framework for learning predictive structures from multiple tasks and unlabeled data. JMLR 6, 1817-1853 (2005)
3. Baluja, S., Rowley, H.: Boosting sex identification performance. International Journal of Computer Vision (2007)
4. Bosch, A., Zisserman, A., Munoz, X.: Image classification using random forests and ferns. In: ICCV 2007 (2008)
5. Caruana, R.: Multitask learning. Machine learning. Machine Learning 28(1), 41-75 (1997)
6. Fei-Fei, L.: Knowledge transfer in learning to recognize visual object classes. In: International Conference on Development and Learning (ICDL) (2006)
7. Fukushima, K., Miyake, S.: Object recognition with features inspired by visual cortex. Pattern Recognition (1982)
8. Grauman, K., Darrell, T.: The pyramid match kernel: Discriminative classification with sets of image features. In: CVPR 2005 (2005)
9. Griffin, G., Holub, A., Perona, P.: Caltech 256 object category dataset. California Institute of Technology 04-1366 (2007)
10. Gutta, S., Huang, J., Jonathon, P., Wechsler, H.: Mixture ofo experts for classification of gender, ethnic origin, and pose of human faces. IEEE Transactions on Neural Networks (2000)
11. Hinton, G., Osindero, S., Teh, Y-W.: A fast learning algorithm for deep belief nets. Neural Computation 18, 1527-1554 (2006)
12. Hubel, D.H., Wiesel, T.N.: Receptive fields, binocular interaction, interaction and functional architecture in the cat's visual cortex. J. Physiology 160, 106-154 (1968)
13. Weston, R.C.J., Ratle, F.: Deep learning via semi-supervised embedding. In: ICML (2008)
14. Lazebnik, S., Schmid, C., Ponce, J.: Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In: CVPR 2006 (2006)
15. LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proceedings of the IEEE 86(11), 2278-2324 (1998)
16. Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2) (2004)
17. Moghaddam, B., Yang, M.-H.: Learning gender with support faces. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) (2002)
18. Mutch, J., Lowe, D.G.: Multiclass object recognition with sparse, localized features. In: CVPR 2006 (2006)
19. Philips, P.J., Flynn, P.J., Scruggs, T., Bower, K.W., Worek, W.: Preliminary face recognition grand challenge results. In: Proceedings of the Sevethn International Conference on Automatic Face and Gesture Recgonition (2006)
20. Ranzato, M., Huang, F.-J., Boureau, Y.-L., LeCun, Y.: Unsupervised learning of invariant feature hierarchies with applications to object recognition. In: CVPR 2007 (2007)
21. Belongie, J.M.S., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509-522 (2002)
22. Serre, T., Wolf, L., Poggio, T.: Object recognition with features inspired by visual cortex. In: CVPR 2005 (2005)
23. Torralba, A., Murphy, K., Freeman, W.: Sharing visual features for multiclass and multiview object detection. IEEE PAMI (2007)