OcrV1, PascalFrancis, Corpus, bibRecord, 000A50

Optical character recognition for self-service banking

Identifieur interne : 000A50 ( PascalFrancis/Corpus ); précédent : 000A49; suivant : 000A51

Optical character recognition for self-service banking

Auteurs : L. D. Jackel ; D. Sharman ; C. E. Stenard ; B. I. Strom ; D. Zuckert

Source :

AT&T technical journal [ 8756-2324 ] ; 1995.

RBID : Pascal:95-0521676

Descripteurs français

Pascal (Inist)
- Reconnaissance forme, Reconnaissance automatique, Traitement caractère, Reconnaissance caractère, Système bancaire, Système optique, Réseau neuronal.

English descriptors

KwdEn :
- Automatic recognition, Bank system, Character processing, Character recognition, Neural networks, Optical systems, Pattern recognition.

Abstract

Self-service automatic teller machines (ATMs) have dramatically altered the ways in which customers interact with banks. ATMs provide the convenience of completing some banking transactions remotely and at any time. AT&T Global Information Solutions (GIS) is the world's leading provider of ATMs. These machines support such familiar services as cash withdrawals and balance inquiries. Further technological development has extended the utility and convenience of ATMs produced by GIS by facilitating check cashing and depositing, as well as direct bill payment, using an on-line system. These enhanced services, discussed in this paper, are made possible primarily through sophisticated optical character recognition (OCR) technology. Developed by an AT&T team that included GIS, AT&T Bell Laboratories Quality, Engineering, Software, and Technologies (QUEST), and AT&T Bell Laboratories Research, OCR technology was crucial to the development of these advanced ATMs.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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A02	`01`			`@0 ATJOEM`
A03		`1`		`@0 ATT tech. j.`
A05				`@2 74`
A06				`@2 4`
A08	`01`	`1`	`ENG`	`@1 Optical character recognition for self-service banking`
A11	`01`	`1`		`@1 JACKEL (L. D.)`
A11	`02`	`1`		`@1 SHARMAN (D.)`
A11	`03`	`1`		`@1 STENARD (C. E.)`
A11	`04`	`1`		`@1 STROM (B. I.)`
A11	`05`	`1`		`@1 ZUCKERT (D.)`
A14	`01`			`@1 AT&T Bell Laboratories, adaptative systems res. dep. @2 Holmdel NJ @3 USA`
A20				`@1 16-24`
A21				`@1 1995`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 513 @5 354000053897630020`
A44				`@0 0000`
A45				`@0 4 ref.`
A47	`01`	`1`		`@0 95-0521676`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 AT&T technical journal`
A66	`01`			`@0 USA`
C01	`01`		`ENG`	@0 Self-service automatic teller machines (ATMs) have dramatically altered the ways in which customers interact with banks. ATMs provide the convenience of completing some banking transactions remotely and at any time. AT&T Global Information Solutions (GIS) is the world's leading provider of ATMs. These machines support such familiar services as cash withdrawals and balance inquiries. Further technological development has extended the utility and convenience of ATMs produced by GIS by facilitating check cashing and depositing, as well as direct bill payment, using an on-line system. These enhanced services, discussed in this paper, are made possible primarily through sophisticated optical character recognition (OCR) technology. Developed by an AT&T team that included GIS, AT&T Bell Laboratories Quality, Engineering, Software, and Technologies (QUEST), and AT&T Bell Laboratories Research, OCR technology was crucial to the development of these advanced ATMs.
C02	`01`	`1`		`@0 001D04A05A`
C03	`01`	`1`	`FRE`	`@0 Reconnaissance forme @5 01`
C03	`01`	`1`	`ENG`	`@0 Pattern recognition @5 01`
C03	`02`	`X`	`FRE`	`@0 Reconnaissance automatique @5 02`
C03	`02`	`X`	`ENG`	`@0 Automatic recognition @5 02`
C03	`02`	`X`	`SPA`	`@0 Reconocimiento automático @5 02`
C03	`03`	`X`	`FRE`	`@0 Traitement caractère @5 03`
C03	`03`	`X`	`ENG`	`@0 Character processing @5 03`
C03	`03`	`X`	`SPA`	`@0 Tratamiento carácter @5 03`
C03	`04`	`1`	`FRE`	`@0 Reconnaissance caractère @5 04`
C03	`04`	`1`	`ENG`	`@0 Character recognition @5 04`
C03	`05`	`X`	`FRE`	`@0 Système bancaire @5 05`
C03	`05`	`X`	`ENG`	`@0 Bank system @5 05`
C03	`05`	`X`	`SPA`	`@0 Sistema bancario @5 05`
C03	`06`	`1`	`FRE`	`@0 Système optique @5 06`
C03	`06`	`1`	`ENG`	`@0 Optical systems @5 06`
C03	`07`	`1`	`FRE`	`@0 Réseau neuronal @5 07`
C03	`07`	`1`	`ENG`	`@0 Neural networks @5 07`
N21				`@1 296`

Format Inist (serveur)

NO :	PASCAL 95-0521676 INIST
ET :	Optical character recognition for self-service banking
AU :	JACKEL (L. D.); SHARMAN (D.); STENARD (C. E.); STROM (B. I.); ZUCKERT (D.)
AF :	AT&T Bell Laboratories, adaptative systems res. dep./Holmdel NJ/Etats-Unis
DT :	Publication en série; Niveau analytique
SO :	AT&T technical journal; ISSN 8756-2324; Coden ATJOEM; Etats-Unis; Da. 1995; Vol. 74; No. 4; Pp. 16-24; Bibl. 4 ref.
LA :	Anglais
EA :	Self-service automatic teller machines (ATMs) have dramatically altered the ways in which customers interact with banks. ATMs provide the convenience of completing some banking transactions remotely and at any time. AT&T Global Information Solutions (GIS) is the world's leading provider of ATMs. These machines support such familiar services as cash withdrawals and balance inquiries. Further technological development has extended the utility and convenience of ATMs produced by GIS by facilitating check cashing and depositing, as well as direct bill payment, using an on-line system. These enhanced services, discussed in this paper, are made possible primarily through sophisticated optical character recognition (OCR) technology. Developed by an AT&T team that included GIS, AT&T Bell Laboratories Quality, Engineering, Software, and Technologies (QUEST), and AT&T Bell Laboratories Research, OCR technology was crucial to the development of these advanced ATMs.
CC :	001D04A05A
FD :	Reconnaissance forme; Reconnaissance automatique; Traitement caractère; Reconnaissance caractère; Système bancaire; Système optique; Réseau neuronal
ED :	Pattern recognition; Automatic recognition; Character processing; Character recognition; Bank system; Optical systems; Neural networks
SD :	Reconocimiento automático; Tratamiento carácter; Sistema bancario
LO :	INIST-513.354000053897630020
ID :	95-0521676

Links to Exploration step

Pascal:95-0521676

Le document en format XML

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<front><div type="abstract" xml:lang="en">Self-service automatic teller machines (ATMs) have dramatically altered the ways in which customers interact with banks. ATMs provide the convenience of completing some banking transactions remotely and at any time. AT&T Global Information Solutions (GIS) is the world's leading provider of ATMs. These machines support such familiar services as cash withdrawals and balance inquiries. Further technological development has extended the utility and convenience of ATMs produced by GIS by facilitating check cashing and depositing, as well as direct bill payment, using an on-line system. These enhanced services, discussed in this paper, are made possible primarily through sophisticated optical character recognition (OCR) technology. Developed by an AT&T team that included GIS, AT&T Bell Laboratories Quality, Engineering, Software, and Technologies (QUEST), and AT&T Bell Laboratories Research, OCR technology was crucial to the development of these advanced ATMs.</div>
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<ET>Optical character recognition for self-service banking</ET>
<AU>JACKEL (L. D.); SHARMAN (D.); STENARD (C. E.); STROM (B. I.); ZUCKERT (D.)</AU>
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<EA>Self-service automatic teller machines (ATMs) have dramatically altered the ways in which customers interact with banks. ATMs provide the convenience of completing some banking transactions remotely and at any time. AT&T Global Information Solutions (GIS) is the world's leading provider of ATMs. These machines support such familiar services as cash withdrawals and balance inquiries. Further technological development has extended the utility and convenience of ATMs produced by GIS by facilitating check cashing and depositing, as well as direct bill payment, using an on-line system. These enhanced services, discussed in this paper, are made possible primarily through sophisticated optical character recognition (OCR) technology. Developed by an AT&T team that included GIS, AT&T Bell Laboratories Quality, Engineering, Software, and Technologies (QUEST), and AT&T Bell Laboratories Research, OCR technology was crucial to the development of these advanced ATMs.</EA>
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Optical character recognition for self-service banking

Optical character recognition for self-service banking

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri