The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
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Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Histograms of Oriented Gradients for Human Detection
Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
(1993) · doi:10.1109/cvpr.1993 · Cited by 17,667
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
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
John Lu, Z. Q. (2010) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2010.00646_6.x · Cited by 12,390
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
Scharstein, D., & Szeliski, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1014573219977 · Cited by 6,740
The German Traffic Sign Recognition Benchmark: A multi-class classification competition
Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2011) · The 2011 International Joint Conference on Neural Networks · doi:10.1109/ijcnn.2011.6033395 · Cited by 1,144
Self-citationA new learning paradigm: Learning using privileged information
Vapnik, V., & Vashist, A. (2009) · Neural Networks · doi:10.1016/j.neunet.2009.06.042 · Cited by 774
Traffic sign recognition with multi-scale Convolutional Networks
Sermanet, P., & LeCun, Y. (2011) · The 2011 International Joint Conference on Neural Networks · doi:10.1109/ijcnn.2011.6033589 · Cited by 759
Cited by
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Practical Black-Box Attacks against Machine Learning
Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z. B., & Swami, A. (2017) · Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security · doi:10.1145/3052973.3053009 · Cited by 3,495
Robust physical-world attacks on deep learning visual classification
Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., Prakash, A., Kohno, T., & Song, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00175 · Cited by 2,173
Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., & Erhan, D. (2016) · arXiv · doi:10.48550/arxiv.1608.06019 · Cited by 1,208
Traffic-Sign Detection and Classification in the Wild
Zhu, Z., Liang, D., Zhang, S., Huang, X., Li, B., & Hu, S. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.232 · Cited by 1,062
Metadata
- Authors
- Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 32
- Pages
- 323-332
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2067713319
- Cited by
- 1,537
- References
- 21
- FWCI
- 35.08
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. https://app.cochat.ai/papers/10.1016/j.neunet.2012.02.016
- The paper
- Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2012). Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Networks. https://doi.org/10.1016/j.neunet.2012.02.016
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
