Titlebook: Machine Learning in Document Analysis and Recognition; Simone Marinai,Hiromichi Fujisawa Book 2008 Springer-Verlag Berlin Heidelberg 2008

砍伐

GLUT

Machine Learning for Signature Verification,samples are available, special learning performs better than general learning (5% higher accuracy). With special learning, verification accuracy increases with the number of samples. An interactive software implementation of signature verification involving both the learning and performance phases i

DEFER

Book 2008ltiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted t

克制

STYX

1860-949X ning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted t978-3-642-09511-5978-3-540-76280-5Series ISSN 1860-949X Series E-ISSN 1860-9503

Mumble

Donato Malerba,Michelangelo Ceci,Margherita Berardi

轻触

凶猛

Sergey Tulyakov,Stefan Jaeger,Venu Govindaraju,David Doermann

Flatus

Sargur N. Srihari,Harish Srinivasan,Siyuan Chen,Matthew J. Beal

mendacity