The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Statistical Learning of Multi-view Face Detection
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A decision-theoretic generalization of on-line learning and an application to boosting
Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466
Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
Friedman, J., Hastie, T., & Tibshirani, R. (2000) · The Annals of Statistics · doi:10.1214/aos/1016218223 · Cited by 6,884
Neural network-based face detection
Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554
Floating search methods in feature selection
Pudil, P., Novovičová, J., & Kittler, J. (1994) · Pattern Recognition Letters · doi:10.1016/0167-8655(94)90127-9 · Cited by 3,098
Face recognition by elastic bunch graph matching
Wiskott, L., Fellous, J.-M., Kuiger, N., & von der Malsburg, C. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.598235 · Cited by 2,883
Improved boosting algorithms using confidence-rated predictions
Schapire, R. E., & Singer, Y. (1998) · Proceedings of the eleventh annual conference on Computational learning theory · doi:10.1145/279943.279960 · Cited by 2,547
Training support vector machines: an application to face detection
Osuna, E., Freund, R., & Girosit, F. (2002) · Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1997.609310 · Cited by 2,486
International Journal of Computer Vision
(2013) · International Journal of Computer Vision · doi:10.1007/11263.1573-1405 · Cited by 2,340
Boosting the margin: a new explanation for the effectiveness of voting methods
Bartlett, P., Freund, Y., Lee, W. S., & Schapire, R. E. (1998) · The Annals of Statistics · doi:10.1214/aos/1024691352 · Cited by 2,306
Feature selection: evaluation, application, and small sample performance
Jain, A., & Zongker, D. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.574797 · Cited by 2,171
View-based and modular eigenspaces for face recognition
Pentland, Moghaddam, & Starner (1994) · Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94 · doi:10.1109/cvpr.1994.323814 · Cited by 1,800
Example-based learning for view-based human face detection
Sung, K.-K., & Poggio, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655648 · Cited by 1,773
A general framework for object detection
Papageorgiou, C. P., Oren, M., & Poggio, T. (2002) · Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271) · doi:10.1109/iccv.1998.710772 · Cited by 1,438
Summed-area tables for texture mapping
Crow, F. C. (1984) · Proceedings of the 11th annual conference on Computer graphics and interactive techniques · doi:10.1145/800031.808600 · Cited by 1,125
A statistical method for 3D object detection applied to faces and cars
Schneiderman, H., & Kanade, T. (2002) · Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662) · doi:10.1109/cvpr.2000.855895 · Cited by 1,059
Hjelmås, E., & Low, B. K. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2001.0921 · Cited by 919
Summed-area tables for texture mapping
Crow, F. C. (1984) · ACM SIGGRAPH Computer Graphics · doi:10.1145/964965.808600 · Cited by 661
Transformation Invariance in Pattern Recognition – Tangent Distance and Tangent Propagation
Simard, P. Y., LeCun, Y. A., Denker, J. S., & Victorri, B. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-35289-8_17 · Cited by 341
Yang, M., Roth, D., & Ahuja, N. (1999) · Cited by 312
Adaptive floating search methods in feature selection
Somol, P., Pudil, P., Novovičová, J., & Paclı́k, P. (1999) · Pattern Recognition Letters · doi:10.1016/s0167-8655(99)00083-5 · Cited by 305
Fleuret, F., & Geman, D. (2001) · International Journal of Computer Vision · doi:10.1023/a:1011113216584 · Cited by 273
Support vector regression and classification based multi-view face detection and recognition
Li, Y., Gong, S., & Liddell, H. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2000.840650 · Cited by 239
Transformation Invariance in Pattern Recognition — Tangent Distance and Tangent Propagation
Simard, P. Y., LeCun, Y. A., Denker, J. S., & Victorri, B. (1998) · Lecture Notes in Computer Science · doi:10.1007/3-540-49430-8_13 · Cited by 229
FotoFile: a consumer multimedia organization and retrieval system
Kuchinsky, A., Pering, C., Creech, M. L., Freeze, D., Serra, B., & Gwizdka, J. (1999) · Proceedings of the SIGCHI conference on Human factors in computing systems the CHI is the limit - CHI '99 · doi:10.1145/302979.303143 · Cited by 202
Joint induction of shape features and tree classifiers
Amit, Y., Geman, D., & Wilder, K. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.632990 · Cited by 197
Face pose discrimination using support vector machines (SVM)
Huang, J., Shao, X., & Wechsler, H. (2002) · Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170) · doi:10.1109/icpr.1998.711102 · Cited by 187
Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks
Simard, P., Bottou, L., Haffner, P., et al. (1998) · Cited by 129
Human Face Recognition and the Face Image Set′s Topology
Bichsel, M., & Pentland, A. ‘. (1994) · CVGIP Image Understanding · doi:10.1006/ciun.1994.1017 · Cited by 117
The application of AdaBoost for distributed, scalable and on-line learning
Fan, W., Stolfo, S. J., & Zhang, J. (1999) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/312129.312283 · Cited by 116
An investigation into face pose distributions
Gong, S., McKenna, S. J., & Collins, J. J. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1996.557275 · Cited by 91
Ng, J., & Gong, S. (2003) · doi:10.1109/ratfg.1999.799218 · Cited by 64
A fast and accurate face detector for indexation of face images
Féraud, R., Bernier, O., Viallet, J. E., & Collobert, M. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2000.840615 · Cited by 58
Pose Discriminiation and Eye Detection Using Support Vector Machines (SVM)
Huang, J. R., Ii, D., Shao, X., & Wechsler, H. (1998) · Springer eBooks · doi:10.1007/978-3-642-72201-1_32 · Cited by 44
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Self-citationFloatBoost learning and statistical face detection
Li, S. Z., & Zhang, Z. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.68 · Cited by 525
Self-citationSupervised Transformer Network for Efficient Face Detection
Chen, D., Hua, G., Wen, F., & Sun, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46454-1_8 · Cited by 185
Face detection and tracking in video sequences using the modifiedcensus transformation
Küblbeck, C., & Ernst, A. (2006) · Image and Vision Computing · doi:10.1016/j.imavis.2005.08.005 · Cited by 178
Hao, Z., Liu, Y., Qin, H., Yan, J., Li, X., & Hu, X. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.207 · Cited by 134
Metadata
- Authors
- Li, S. Z., Zhu, L., Zhang, Z., Blake, A., Zhang, H., & Shum, H.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2002
- Pages
- 67-81
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1555563476
- Cited by
- 398
- References
- 34
- FWCI
- 22.12
- Type
- conference paper
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.