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Optical character recognition for self-service banking

Identifieur interne : 002D51 ( Main/Merge ); précédent : 002D50; suivant : 002D52

Optical character recognition for self-service banking

Auteurs : L. D. Jackel [États-Unis] ; D. Sharman ; C. E. Stenard ; B. I. Strom ; D. Zuckert

Source :

RBID : Pascal:95-0521676

Descripteurs français

English descriptors

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.

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Pascal:95-0521676

Le document en format XML

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<title xml:lang="en" level="a">Optical character recognition for self-service banking</title>
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<name sortKey="Jackel, L D" sort="Jackel, L D" uniqKey="Jackel L" first="L. D." last="Jackel">L. D. Jackel</name>
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<s1>AT&T Bell Laboratories, adaptative systems res. dep.</s1>
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<country>États-Unis</country>
<wicri:noRegion>Holmdel NJ</wicri:noRegion>
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<name sortKey="Sharman, D" sort="Sharman, D" uniqKey="Sharman D" first="D." last="Sharman">D. Sharman</name>
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<name sortKey="Strom, B I" sort="Strom, B I" uniqKey="Strom B" first="B. I." last="Strom">B. I. Strom</name>
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<term>Automatic recognition</term>
<term>Bank system</term>
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<term>Character recognition</term>
<term>Neural networks</term>
<term>Optical systems</term>
<term>Pattern recognition</term>
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<keywords scheme="Pascal" xml:lang="fr">
<term>Reconnaissance forme</term>
<term>Reconnaissance automatique</term>
<term>Traitement caractère</term>
<term>Reconnaissance caractère</term>
<term>Système bancaire</term>
<term>Système optique</term>
<term>Réseau neuronal</term>
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<term>Système bancaire</term>
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<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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