A neural network approach to handprint character recognition

L. D. Jackel; C. E. Stenard; H. S. Baird; B. Boser; J. Bromley; C. J.C. Burges; J. S. Denker; H. P. Graf; D. Henderson; R. E. Howard; W. Hubbard; Y. leCun; O. Matan; E. Pednault; W. Satterfield; E. Sackinger; T. Thompson

A neural network approach to handprint character recognition

L. D. Jackel, C. E. Stenard, H. S. Baird, B. Boser, J. Bromley, C. J.C. Burges, J. S. Denker, H. P. Graf, D. Henderson, R. E. Howard, W. Hubbard, Y. leCun, O. Matan, E. Pednault, W. Satterfield, E. Sackinger, T. Thompson

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The authors outline OCR (optical character recognition) technology developed at AT&T Bell Laboratories, including a recognition network that learns feature extraction kernels and a custom VLSI chip that is designed for neural-net image processing. It is concluded that both high speed and high accuracy can be obtained using neural-net methods for character recognition. Networks can be designed that learn their own feature extraction kernels. Special-purpose neural-net chips combined with digital signal processors can quickly evaluate character-recognition neural nets. This high speed is particularly useful for recognition-based segmentation of character strings.

Original language	English (US)
Title of host publication	Digest of Papers - IEEE Computer Society International Conference
Publisher	Publ by IEEE
Pages	472-475
Number of pages	4
ISBN (Print)	0818621346
State	Published - 1991
Event	36th IEEE Computer Society International Conference - COMPCON Sping '91 - San Francisco, CA, USA Duration: Feb 25 1991 → Mar 1 1991

Publication series

Name	Digest of Papers - IEEE Computer Society International Conference

Other

Other	36th IEEE Computer Society International Conference - COMPCON Sping '91
City	San Francisco, CA, USA
Period	2/25/91 → 3/1/91

ASJC Scopus subject areas

General Engineering

Cite this

Jackel, L. D., Stenard, C. E., Baird, H. S., Boser, B., Bromley, J., Burges, C. J. C., Denker, J. S., Graf, H. P., Henderson, D., Howard, R. E., Hubbard, W., leCun, Y., Matan, O., Pednault, E., Satterfield, W., Sackinger, E., & Thompson, T. (1991). A neural network approach to handprint character recognition. In Digest of Papers - IEEE Computer Society International Conference (pp. 472-475). (Digest of Papers - IEEE Computer Society International Conference). Publ by IEEE.

A neural network approach to handprint character recognition. / Jackel, L. D.; Stenard, C. E.; Baird, H. S. et al.
Digest of Papers - IEEE Computer Society International Conference. Publ by IEEE, 1991. p. 472-475 (Digest of Papers - IEEE Computer Society International Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jackel, LD, Stenard, CE, Baird, HS, Boser, B, Bromley, J, Burges, CJC, Denker, JS, Graf, HP, Henderson, D, Howard, RE, Hubbard, W, leCun, Y, Matan, O, Pednault, E, Satterfield, W, Sackinger, E & Thompson, T 1991, A neural network approach to handprint character recognition. in Digest of Papers - IEEE Computer Society International Conference. Digest of Papers - IEEE Computer Society International Conference, Publ by IEEE, pp. 472-475, 36th IEEE Computer Society International Conference - COMPCON Sping '91, San Francisco, CA, USA, 2/25/91.

@inproceedings{12b2f297888c456896ade685a3b6b05a,

title = "A neural network approach to handprint character recognition",

abstract = "The authors outline OCR (optical character recognition) technology developed at AT&T Bell Laboratories, including a recognition network that learns feature extraction kernels and a custom VLSI chip that is designed for neural-net image processing. It is concluded that both high speed and high accuracy can be obtained using neural-net methods for character recognition. Networks can be designed that learn their own feature extraction kernels. Special-purpose neural-net chips combined with digital signal processors can quickly evaluate character-recognition neural nets. This high speed is particularly useful for recognition-based segmentation of character strings.",

author = "Jackel, {L. D.} and Stenard, {C. E.} and Baird, {H. S.} and B. Boser and J. Bromley and Burges, {C. J.C.} and Denker, {J. S.} and Graf, {H. P.} and D. Henderson and Howard, {R. E.} and W. Hubbard and Y. leCun and O. Matan and E. Pednault and W. Satterfield and E. Sackinger and T. Thompson",

year = "1991",

language = "English (US)",

isbn = "0818621346",

series = "Digest of Papers - IEEE Computer Society International Conference",

publisher = "Publ by IEEE",

pages = "472--475",

booktitle = "Digest of Papers - IEEE Computer Society International Conference",

note = "36th IEEE Computer Society International Conference - COMPCON Sping '91 ; Conference date: 25-02-1991 Through 01-03-1991",

}

TY - GEN

T1 - A neural network approach to handprint character recognition

AU - Jackel, L. D.

AU - Stenard, C. E.

AU - Baird, H. S.

AU - Boser, B.

AU - Bromley, J.

AU - Burges, C. J.C.

AU - Denker, J. S.

AU - Graf, H. P.

AU - Henderson, D.

AU - Howard, R. E.

AU - Hubbard, W.

AU - leCun, Y.

AU - Matan, O.

AU - Pednault, E.

AU - Satterfield, W.

AU - Sackinger, E.

AU - Thompson, T.

PY - 1991

Y1 - 1991

N2 - The authors outline OCR (optical character recognition) technology developed at AT&T Bell Laboratories, including a recognition network that learns feature extraction kernels and a custom VLSI chip that is designed for neural-net image processing. It is concluded that both high speed and high accuracy can be obtained using neural-net methods for character recognition. Networks can be designed that learn their own feature extraction kernels. Special-purpose neural-net chips combined with digital signal processors can quickly evaluate character-recognition neural nets. This high speed is particularly useful for recognition-based segmentation of character strings.

AB - The authors outline OCR (optical character recognition) technology developed at AT&T Bell Laboratories, including a recognition network that learns feature extraction kernels and a custom VLSI chip that is designed for neural-net image processing. It is concluded that both high speed and high accuracy can be obtained using neural-net methods for character recognition. Networks can be designed that learn their own feature extraction kernels. Special-purpose neural-net chips combined with digital signal processors can quickly evaluate character-recognition neural nets. This high speed is particularly useful for recognition-based segmentation of character strings.

UR - http://www.scopus.com/inward/record.url?scp=0026368669&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026368669&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0026368669

SN - 0818621346

T3 - Digest of Papers - IEEE Computer Society International Conference

SP - 472

EP - 475

BT - Digest of Papers - IEEE Computer Society International Conference

PB - Publ by IEEE

T2 - 36th IEEE Computer Society International Conference - COMPCON Sping '91

Y2 - 25 February 1991 through 1 March 1991

ER -

A neural network approach to handprint character recognition

Abstract

Publication series

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this