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Volumn , Issue , 2012, Pages 2095-2099

A Grassmann manifold-based domain adaptation approach

Author keywords

[No Author keywords available]

Indexed keywords

CROSS-DOMAIN; DOMAIN ADAPTATION; FEATURE PROJECTION; TARGET DOMAIN; TRAINING AND TESTING;

EID: 84874576262     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (31)

References (13)
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  • 3
    • 70450185098 scopus 로고    scopus 로고
    • Domain transfer SVM for video concept detection
    • L. Duan, I. W.-H. Tsang, D. Xu, and S. J. Maybank. Domain transfer SVM for video concept detection. In CVPR, 2009.
    • (2009) CVPR
    • Duan, L.1    Tsang, I.W.-H.2    Xu, D.3    Maybank, S.J.4
  • 5
    • 84866657270 scopus 로고    scopus 로고
    • Geodesic flow kernel for unsupervised domain adaptation
    • B. Gong, Y. Shi, F. Sha, and K. Grauman. Geodesic flow kernel for unsupervised domain adaptation. In CVPR, 2012.
    • (2012) CVPR
    • Gong, B.1    Shi, Y.2    Sha, F.3    Grauman, K.4
  • 6
    • 84863396387 scopus 로고    scopus 로고
    • Domain adaptation for object recognition: An unsupervised approach
    • R. Gopalan, R. Li, and R. Chellappa. Domain adaptation for object recognition: An unsupervised approach. In ICCV, 2011.
    • (2011) ICCV
    • Gopalan, R.1    Li, R.2    Chellappa, R.3
  • 7
    • 68349087851 scopus 로고    scopus 로고
    • Cross-domain learning methods for high-level visual concept classification
    • W. Jiang, E. Zavesky, S.-F. Chang, and A. C. Loui. Cross-domain learning methods for high-level visual concept classification. In ICIP, 2008.
    • (2008) ICIP
    • Jiang, W.1    Zavesky, E.2    Chang, S.-F.3    Loui, A.C.4
  • 8
    • 80052895155 scopus 로고    scopus 로고
    • What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
    • B. Kulis, K. Saenko, and T. Darrell. What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. In CVPR, 2011.
    • (2011) CVPR
    • Kulis, B.1    Saenko, K.2    Darrell, T.3
  • 9
    • 78149301639 scopus 로고    scopus 로고
    • Adapting visual category models to new domains
    • K. Saenko, B. Kulis, M. Fritz, and T. Darrell. Adapting visual category models to new domains. In ECCV, 2010.
    • (2010) ECCV
    • Saenko, K.1    Kulis, B.2    Fritz, M.3    Darrell, T.4
  • 10
    • 0347380229 scopus 로고    scopus 로고
    • The cmu pose, illumination, and expression database
    • T. Sim, S. Baker, and M. Bsat. The cmu pose, illumination, and expression database. TPAMI, 2003.
    • (2003) TPAMI
    • Sim, T.1    Baker, S.2    Bsat, M.3
  • 11
    • 80053126879 scopus 로고    scopus 로고
    • Statistical computations on grassmann and stiefel manifolds for image and video-based recognition
    • P. K. Turaga, A. Veeraraghavan, A. Srivastava, and R. Chellappa. Statistical computations on grassmann and stiefel manifolds for image and video-based recognition. TPAMI, 2011.
    • (2011) TPAMI
    • Turaga, P.K.1    Veeraraghavan, A.2    Srivastava, A.3    Chellappa, R.4
  • 13
    • 37849026107 scopus 로고    scopus 로고
    • Cross-domain video concept detection using adaptive SVMs
    • J. Yang, R. Yan, and A. G. Hauptmann. Cross-domain video concept detection using adaptive SVMs. In ACM Multimedia, 2007.
    • (2007) ACM Multimedia
    • Yang, J.1    Yan, R.2    Hauptmann, A.G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.