The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Learning gender with support faces
Abstract
Nonlinear support vector machines (SVMs) are investigated for appearance-based gender classification with low-resolution "thumbnail" faces processed from 1,755 images from the FERET (FacE REcognition Technology) face database. The performance of SVMs (3.4% error) is shown to be superior to traditional pattern classifiers (linear, quadratic, Fisher linear discriminant, nearest-neighbor) as well as more modern techniques, such as radial basis function (RBF) classifiers and large ensemble-RBF networks. Furthermore, the difference in classification performance with low-resolution "thumbnails" (21/spl times/12 pixels) and the corresponding higher-resolution images (84/spl times/48 pixels) was found to be only 1%, thus demonstrating robustness and stability with respect to scale and the degree of facial detail.
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Cites
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Cited by
Attribute and simile classifiers for face verification
Kumar, N., Berg, A. C., Belhumeur, P. N., & Nayar, S. K. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459250 · Cited by 1,361
A Survey of Face Recognition Techniques
Jafri, R., & Arabnia, H. R. (2009) · Journal of Information Processing Systems · doi:10.3745/jips.2009.5.2.041 · Cited by 677
Describable Visual Attributes for Face Verification and Image Search
Kumar, N., Berg, A., Belhumeur, P. N., & Nayar, S. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.48 · Cited by 434
More generality in efficient multiple kernel learning
Varma, M., & Babu, B. R. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553510 · Cited by 398
Fire detection based on vision sensor and support vector machines
Ko, B. C., Cheong, K.-H., & Nam, J.-Y. (2009) · Fire Safety Journal · doi:10.1016/j.firesaf.2008.07.006 · Cited by 388
Metadata
- Authors
- Moghaddam, B., & Yang, M.-H.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2002-05
- Volume
- 24
- Issue
- 5
- Pages
- 707-711
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2101392314
- Cited by
- 598
- References
- 3
- FWCI
- 11.61
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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