메뉴 건너뛰기




Volumn 9915 LNCS, Issue , 2016, Pages 443-450

Deep CORAL: Correlation alignment for deep domain adaptation

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION; LINEAR TRANSFORMATIONS;

EID: 85006058961     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-49409-8_35     Document Type: Conference Paper
Times cited : (2864)

References (23)
  • 1
    • 84902256759 scopus 로고    scopus 로고
    • DLID: Deep learning for domain adaptation by interpolating between domains
    • Chopra, S., Balakrishnan, S., Gopalan, R.: DLID: deep learning for domain adaptation by interpolating between domains. In: ICML Workshop (2013)
    • (2013) ICML Workshop
    • Chopra, S.1    Balakrishnan, S.2    Gopalan, R.3
  • 4
    • 84898798531 scopus 로고    scopus 로고
    • Unsupervised visual domain adaptation using subspace alignment
    • Fernando, B., Habrard, A., Sebban, M., Tuytelaars, T.: Unsupervised visual domain adaptation using subspace alignment. In: ICCV (2013)
    • (2013) ICCV
    • Fernando, B.1    Habrard, A.2    Sebban, M.3    Tuytelaars, T.4
  • 5
    • 84969802531 scopus 로고    scopus 로고
    • Unsupervised domain adaptation by backpropagation
    • Ganin, Y., Lempitsky, V.: Unsupervised domain adaptation by backpropagation. In: ICML (2015)
    • (2015) ICML
    • Ganin, Y.1    Lempitsky, V.2
  • 6
    • 84866657270 scopus 로고    scopus 로고
    • Geodesic flow kernel for unsupervised domain adaptation
    • Gong, B., Shi, Y., Sha, F., Grauman, K.: Geodesic flow kernel for unsupervised domain adaptation. In: CVPR (2012)
    • (2012) CVPR
    • Gong, B.1    Shi, Y.2    Sha, F.3    Grauman, K.4
  • 7
    • 84863396387 scopus 로고    scopus 로고
    • Domain adaptation for object recognition: An unsupervised approach
    • Gopalan, R., Li, R., Chellappa, R.: Domain adaptation for object recognition: an unsupervised approach. In: ICCV (2011)
    • (2011) ICCV
    • Gopalan, R.1    Li, R.2    Chellappa, R.3
  • 8
    • 80053439042 scopus 로고    scopus 로고
    • Learning from multiple outlooks
    • Harel, M., Mannor, S.: Learning from multiple outlooks. In: ICML (2011)
    • (2011) ICML
    • Harel, M.1    Mannor, S.2
  • 11
    • 84860538689 scopus 로고    scopus 로고
    • Instance weighting for domain adaptation in NLP
    • Jiang, J., Zhai, C.: Instance weighting for domain adaptation in NLP. In: ACL (2007)
    • (2007) ACL
    • Jiang, J.1    Zhai, C.2
  • 12
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS (2012)
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 13
    • 84969549144 scopus 로고    scopus 로고
    • Learning transferable features with deep adaptation networks
    • Long, M., Cao, Y., Wang, J., Jordan, M.I.: Learning transferable features with deep adaptation networks. In: ICML (2015)
    • (2015) ICML
    • Long, M.1    Cao, Y.2    Wang, J.3    Jordan, M.I.4
  • 14
    • 78751696249 scopus 로고    scopus 로고
    • Domain adaptation via transfer component analysis
    • Pan, S.J., Tsang, I.W., Kwok, J.T., Yang, Q.: Domain adaptation via transfer component analysis. In: IJCAI (2009)
    • (2009) IJCAI
    • Pan, S.J.1    Tsang, I.W.2    Kwok, J.T.3    Yang, Q.4
  • 15
    • 84973922826 scopus 로고    scopus 로고
    • Learning deep object detectors from 3D models
    • Peng, X., Sun, B., Ali, K., Saenko, K.: Learning deep object detectors from 3D models. In: ICCV (2015)
    • (2015) ICCV
    • Peng, X.1    Sun, B.2    Ali, K.3    Saenko, K.4
  • 17
    • 78149318752 scopus 로고    scopus 로고
    • Adapting visual category models to new domains
    • Daniilidis, K., Maragos, P., Paragios, N. (eds.), Springer, Heidelberg
    • Saenko, K., Kulis, B., Fritz, M., Darrell, T.: Adapting visual category models to new domains. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6316, pp. 213-226. Springer, Heidelberg (2010). doi:10.1007/ 978-3-642-15561-1_16
    • (2010) ECCV 2010. LNCS , vol.6316 , pp. 213-226
    • Saenko, K.1    Kulis, B.2    Fritz, M.3    Darrell, T.4
  • 18
    • 84990048974 scopus 로고    scopus 로고
    • Return of frustratingly easy domain adaptation
    • Sun, B., Feng, J., Saenko, K.: Return of frustratingly easy domain adaptation. In: AAAI (2016)
    • (2016) AAAI
    • Sun, B.1    Feng, J.2    Saenko, K.3
  • 20
    • 85031103438 scopus 로고    scopus 로고
    • From virtual to reality: Fast adaptation of virtual object detectors to real domains
    • Sun, B., Saenko, K.: From virtual to reality: fast adaptation of virtual object detectors to real domains. In: BMVC (2014)
    • (2014) BMVC
    • Sun, B.1    Saenko, K.2
  • 21
    • 84962005349 scopus 로고    scopus 로고
    • Subspace distribution alignment for unsupervised domain adaptation
    • Sun, B., Saenko, K.: Subspace distribution alignment for unsupervised domain adaptation. In: BMVC (2015)
    • (2015) BMVC
    • Sun, B.1    Saenko, K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.