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Volumn 2, Issue , 2007, Pages 411-414

Feature selection for iris recognition with AdaBoost

Author keywords

AdaBoost; Biometrics; Feature extraction; Iris recognition

Indexed keywords

ADABOOST; ADABOOST ALGORITHMS; BOOSTING ALGORITHMS; COMPUTATION TIME; FEATURE SELECTION (FS); INFORMATION HIDING; INTERNATIONAL (CO); INTERNATIONAL CONFERENCES; IRIS RECOGNITION; MULTIMEDIA SIGNAL PROCESSING; REAL EXPERIMENTS; RECOGNITION ACCURACY; WEAK CLASSIFIERS;

EID: 47349123255     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IIHMSP.2007.4457736     Document Type: Conference Paper
Times cited : (5)

References (9)
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  • 3
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    • Freund, Y.1    Schapire, R.E.2
  • 5
    • 2942628075 scopus 로고    scopus 로고
    • Efficient iris recognition by characterizing key local variations
    • L. Ma, T. Tan, Y. Wang, and D. Zhang. Efficient iris recognition by characterizing key local variations. IEEE Trans. on Image Processing, 13(6):739-750, 2004.
    • (2004) IEEE Trans. on Image Processing , vol.13 , Issue.6 , pp. 739-750
    • Ma, L.1    Tan, T.2    Wang, Y.3    Zhang, D.4
  • 7
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    • Toward noncooperative iris recognition: A classification approach using multiple signatures
    • H. Proença and L. A. Alexandre. Toward noncooperative iris recognition: A classification approach using multiple signatures. IEEE Trans. Pattern Anal. Machine Intell., 29(4):607-612, 2007.
    • (2007) IEEE Trans. Pattern Anal. Machine Intell , vol.29 , Issue.4 , pp. 607-612
    • Proença, H.1    Alexandre, L.A.2
  • 8
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    • Iris recognition: An emerging biometric technology
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    • Wildes, R.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.