OcrV1, Main, Exploration, bibRecordById, Pascal:95-0521676

Optical Character Recognition for Self‐Service Banking

Identifieur interne : 002A71 ( Main/Exploration ); précédent : 002A70; suivant : 002A72

Optical Character Recognition for Self‐Service Banking

Auteurs : Lawrence D. Jackel ; David Sharman ; Charles E. Stenard ; B. Ivan Strom ; Derek Zuckert

Source :

AT&T Technical Journal [ 8756-2324 ] ; 1995-07-08.

RBID : ISTEX:5A194881B89299465769A0259B755B2B509B7DD7

Descripteurs français

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

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.

Url:

https://api.istex.fr/document/5A194881B89299465769A0259B755B2B509B7DD7/fulltext/pdf

DOI: 10.1002/j.1538-7305.1995.tb00189.x

Affiliations:

Le document en format XML

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<keywords scheme="Pascal" xml:lang="fr"><term>Reconnaissance automatique</term>
<term>Reconnaissance caractère</term>
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<term>Système bancaire</term>
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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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Serveur d'exploration sur l'OCR

Optical Character Recognition for Self‐Service Banking

Optical Character Recognition for Self‐Service Banking

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

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