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11

AVBPA
2001
Springer

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Fingerprint Classification with Combinations of Support Vector Machines

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Fingerprint Classification with Combinations of Support Vector Machines

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Abstract. We report about some experiments on the fingerprint database NIST-4 using different combinations of Support Vector Machine (SVM) classifiers. Images have been preprocessed using the feature extraction technique as in [10]. Our best classification accuracy is 89.3 per

Yuan Yao, Paolo Frasconi, Massimiliano Pontil

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AVBPA 2001 | Biometrics | Feature Extraction Technique | Fingerprint Database | Support Vector Machine |

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Added	23 Aug 2010
Updated	23 Aug 2010
Type	Conference
Year	2001
Where	AVBPA
Authors	Yuan Yao, Paolo Frasconi, Massimiliano Pontil

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