A.N.N. Based Approach to Mass Biometry Taking Advantage from Modularity
| Autor: | Kurosh Madani, Abdennasser Chebira, Véronique Amarger |
|---|---|
| Přispěvatelé: | Amirat, Yacine, SYNAPSE, Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Laboratoire Images, Signaux et Systèmes Intelligents ( LISSI ), Université Paris-Est Créteil Val-de-Marne - Paris 12 ( UPEC UP12 ) -Université Paris-Est Créteil Val-de-Marne - Paris 12 ( UPEC UP12 ) |
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
020301 aerospace & aeronautics
Artificial neural network Biometrics business.industry Computer science [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Context (language use) 02 engineering and technology Machine learning computer.software_genre [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Modularity Set (abstract data type) [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] 0203 mechanical engineering 0202 electrical engineering electronic engineering information engineering Public security 020201 artificial intelligence & image processing Artificial intelligence IBM Suspect business computer ComputingMilieux_MISCELLANEOUS |
| Zdroj: | Proc. of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Proc. of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, 2009, Salamanca, Spain. pp.1312-1319 Proc. of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, 2009, Salamanca, Spain. LNCS series, vol. 5517, Springer, pp.1312-1319, 2009 Lecture Notes in Computer Science ISBN: 9783642024771 IWANN (1) |
| Popis: | Over the recent years, new public security tendency to fit up public areas with biometric devices has emerged new requirements in biometric recognition dealing with what we call here "mass biometry". If the goal in "individual biometry" is to authenticate and/or identify an individual within a set of favored folks, the aim in "mass biometry" is to classify a suspect individual or behavior within a flow of mass customary information. In this case, the ability of handling relatively poor information and the skill of high speed processing become chief requirements. These antagonistic requests make the "mass biometry" and related applications among the most challenging frames. In this paper we present an ANN based system in a "mass biometry" context using facial biometric features. The proposed system takes advantage from kernel functions ANN model and IBM ZISC based hardware. Experimental results validating our system are presented and discussed. |
| Databáze: | OpenAIRE |
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