CoChat
Sign Up
Cited by 37Handwritten Text Recognition TechniquesVehicle License Plate RecognitionAdvanced Neural Network Applications

The DOI matches its Crossref record, with a small difference in title or year.

Shortest path segmentation: a method for training a neural network to recognize character strings

Burges, C.J.C., Matan, O., Le Cun, Y., Denker, J.S., Jackel, L.D., Stenard, C.E., Nohl, C.R., Ben, J.I.·2003·[Proceedings 1992] IJCNN International Joint Conference on Neural Networks
DOI 10.1109/ijcnn.1992.227175
Open this paper in CoChat — free account

Abstract

The authors describe a method which combines dynamic programming and a neural network recognizer for segmenting and recognizing character strings. The method selects the optimal consistent combination of cuts from a set of candidate cuts generated using heuristics. The optimal segmentation is found by representing the image, the candidate segments, and their scores as a graph in which the shortest path corresponds to the optimal interpretation. The scores are given by neural net outputs for each segment. A significant advantage of the method is that the labor required to segment images manually is eliminated. The system was trained on approximately 7000 unsegmented handwritten zip codes provided by the United States Postal Service. The system has achieved a per-zip-code raw recognition rate of 81% on a 2368 handwritten zip-code test set.>

Overview

Integrity signals

Registry

Crossref · 10.1109/ijcnn.1992.227175

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 11

  1. martin, 1991, Recognizing Overlapping Hand-Printed Characters by Centered-Object Integrated Segmentation and Recognition, Proc Neural Inform Processing Syst Conf
  2. 10.1109/2.144441 · DOI · Paper page
  3. 10.1109/5.18626 · DOI · Paper page
  4. lecolinet, 1989, A New System for Automatic Segmentation and Recognition of Unconstrained Handwritten ZIP Codes, Scandinavian Conference on Image Analysis
  5. 10.1109/PROC.1973.9030 · DOI
  6. keeler, 1990, Integrated Segmentation and Recognition of Hand-Printed Numerals, Proc Neural Inform Processing Syst Conf
  7. fenrich, 1990, United States Postal Service - Advanced Technology Conference, 1
  8. 10.1109/ICPR.1990.119325 · DOI
  9. shridhar, 1990, Session Chairman, Session on Hand Written Digit Recognition, United States Postal Service - Advanced Technology Conference
  10. bridle, 1989, Neuro-computing Algorithms Architectures and Applications
  11. fenrich, 1991, Segmentation of Automatically Located Handwritten Words, International Workshop on Frontiers in Handwriting Recognition

Cited by

Sorted by citations

See all 37

Metadata

Authors
Burges, C. J. C., Matan, O., Le Cun, Y., Denker, J. S., Jackel, L. D., Stenard, C. E., Nohl, C. R., & Ben, J. I.
Affiliations
AT&T (United States) (US)
ORCID
Jackel, L.D.
Venue
[Proceedings 1992] IJCNN International Joint Conference on Neural Networks
Publisher
IEEE
Published
2003-01-02
Volume
3
Pages
165-172
ISSN
2161-4407 (ISSN-L)
DOI
10.1109/ijcnn.1992.227175
OpenAlex
W2132793646
Cited by
37
References
0
Citations by year
2020: 1 · 2018: 1 · 2016: 1 · 2014: 1 · 2013: 3
FWCI
0.99
Type
conference paper
Language
en
Open access
closed
Locations
International Joint Conference on Neural Networks (IJCNN) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Handwritten Text Recognition Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Vehicle License Plate Recognition
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords
dynamic programming, graph-based segmentation, handwritten character recognition

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: Shortest path segmentation: a method for training a neural network to recognize character strings. https://app.cochat.ai/papers/10.1109/ijcnn.1992.227175
The paper
Burges, C. J. C., Matan, O., Le Cun, Y., Denker, J. S., Jackel, L. D., Stenard, C. E., Nohl, C. R., & Ben, J. I. (2003). Shortest path segmentation: a method for training a neural network to recognize character strings. [Proceedings 1992] IJCNN International Joint Conference on Neural Networks. https://doi.org/10.1109/ijcnn.1992.227175