The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Comparison of classifier methods: a case study in handwritten digit recognition
Abstract
This paper compares the performance of several classifier algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also training time, recognition time, and memory requirements. When available, we report measurements of the fraction of patterns that must be rejected so that the remaining patterns have misclassification rates less than a given threshold.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Strength of Weak Learnability
Schapire, R. E. (1990) · Machine Learning · doi:10.1007/bf00116037 · Cited by 4,600
Cited by
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
Self-citationArjovsky, M., Bottou, L., Gulrajani, I., & Lopez-Paz, D. (2019) · arXiv · doi:10.48550/arxiv.1907.02893 · Cited by 927
Self-citationKotsia, I., & Pitas, I. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.884954 · Cited by 687
Cold Case: The Lost MNIST Digits
Yadav, C., & Bottou, L. (2019) · arXiv · doi:10.48550/arxiv.1905.10498 · Cited by 69
Self-citation
Metadata
- Authors
- Bottou, L., Cortes, C., Denker, J. S., Drucker, H., Guyon, I., Jackel, L. D., LeCun, Y., Muller, U. A., Sackinger, E., Simard, P., & Vapnik, V.
- Venue
- Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5)
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-17
- Volume
- 2
- Pages
- 77-82
- OpenAlex
- W2168228682
- Cited by
- 626
- References
- 1
- FWCI
- 10.26
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Comparison of classifier methods: a case study in handwritten digit recognition. https://app.cochat.ai/papers/10.1109/icpr.1994.576879
- The paper
- Bottou, L., Cortes, C., Denker, J. S., Drucker, H., Guyon, I., Jackel, L. D., LeCun, Y., Muller, U. A., Sackinger, E., Simard, P., & Vapnik, V. (2002). Comparison of classifier methods: a case study in handwritten digit recognition. Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5). https://doi.org/10.1109/icpr.1994.576879
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.
