Optical character recognition for self-service banking
Identifieur interne : 002D51 ( Main/Merge ); précédent : 002D50; suivant : 002D52Optical character recognition for self-service banking
Auteurs : L. D. Jackel [États-Unis] ; D. Sharman ; C. E. Stenard ; B. I. Strom ; D. ZuckertSource :
- AT&T technical journal [ 8756-2324 ] ; 1995.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Système bancaire.
English descriptors
- KwdEn :
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:95-0521676Le document en format XML
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<author><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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<s2>Holmdel NJ</s2>
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<country>États-Unis</country>
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<author><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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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Automatic recognition</term>
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<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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<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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