메뉴 건너뛰기




Volumn 7, Issue 8, 2014, Pages 649-660

Effective multimodal retrieval based on stacked auto-encoders

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; LARGE DATASET; LEARNING SYSTEMS; MAPPING; SEMANTICS;

EID: 84901787656     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/2732296.2732301     Document Type: Conference Paper
Times cited : (160)

References (27)
  • 1
    • 77955989956 scopus 로고    scopus 로고
    • Data fusion through cross-modality metric learning using similarity-sensitive hashing
    • M. M. Bronstein, A. M. Bronstein, F. Michel, and N. Paragios. Data fusion through cross-modality metric learning using similarity-sensitive hashing. In CVPR, pages 3594-3601, 2010.
    • (2010) CVPR , pp. 3594-3601
    • Bronstein, M.M.1    Bronstein, A.M.2    Michel, F.3    Paragios, N.4
  • 4
    • 84901772283 scopus 로고    scopus 로고
    • Saturating auto-encoder
    • CoRR, abs/1301.3577
    • R. Goroshin and Y. LeCun. Saturating auto-encoder. CoRR, abs/1301.3577, 2013.
    • (2013)
    • Goroshin, R.1    LeCun, Y.2
  • 5
    • 78650474133 scopus 로고    scopus 로고
    • A Practical Guide to Training Restricted Boltzmann Machines
    • Technical report
    • G. Hinton. A Practical Guide to Training Restricted Boltzmann Machines. Technical report, 2010.
    • (2010)
    • Hinton, G.1
  • 6
    • 0041664272 scopus 로고    scopus 로고
    • Index-driven similarity search in metric spaces
    • G. R. Hjaltason and H. Samet. Index-driven similarity search in metric spaces. ACM Trans. Database Syst., 28(4):517-580, 2003.
    • (2003) ACM Trans. Database Syst , vol.28 , Issue.4 , pp. 517-580
    • Hjaltason, G.R.1    Samet, H.2
  • 8
    • 77956002520 scopus 로고    scopus 로고
    • Learning multiple layers of features from tiny images
    • Technical report
    • A. Krizhevsky. Learning multiple layers of features from tiny images. Technical report, 2009.
    • (2009)
    • Krizhevsky, A.1
  • 9
    • 84866034209 scopus 로고    scopus 로고
    • Learning hash functions for cross-view similarity search
    • S. Kumar and R. Udupa. Learning hash functions for cross-view similarity search. In IJCAI, pages 1360-1365, 2011.
    • (2011) IJCAI , pp. 1360-1365
    • Kumar, S.1    Udupa, R.2
  • 12
    • 84883119531 scopus 로고    scopus 로고
    • A low rank structural large margin method for cross-modal ranking
    • X. Lu, F. Wu, S. Tang, Z. Zhang, X. He, and Y. Zhuang. A low rank structural large margin method for cross-modal ranking. In SIGIR, pages 433-442, 2013.
    • (2013) SIGIR , pp. 433-442
    • Lu, X.1    Wu, F.2    Tang, S.3    Zhang, Z.4    He, X.5    Zhuang, Y.6
  • 14
    • 34548080780 scopus 로고    scopus 로고
    • Introduction to information retrieval
    • Cambridge University Press
    • C. D. Manning, P. Raghavan, and H. Schütze. Introduction to information retrieval, pages 151-175. Cambridge University Press, 2008.
    • (2008) , pp. 151-175
    • Manning, C.D.1    Raghavan, P.2    Schütze, H.3
  • 17
    • 80053460450 scopus 로고    scopus 로고
    • Contractive auto-encoders: Explicit invariance during feature extraction
    • S. Rifai, P. Vincent, X. Muller, X. Glorot, and Y. Bengio. Contractive auto-encoders: Explicit invariance during feature extraction. In ICML, pages 833-840, 2011.
    • (2011) ICML , pp. 833-840
    • Rifai, S.1    Vincent, P.2    Muller, X.3    Glorot, X.4    Bengio, Y.5
  • 19
    • 80053261327 scopus 로고    scopus 로고
    • Semi-supervised recursive autoencoders for predicting sentiment distributions
    • R. Socher, J. Pennington, E. H. Huang, A. Y. Ng, and C. D. Manning. Semi-supervised recursive autoencoders for predicting sentiment distributions. In EMNLP, pages 151-161, 2011.
    • (2011) EMNLP , pp. 151-161
    • Socher, R.1    Pennington, J.2    Huang, E.H.3    Ng, A.Y.4    Manning, C.D.5
  • 20
    • 84880548516 scopus 로고    scopus 로고
    • Inter-media hashing for large-scale retrieval from heterogeneous data sources
    • J. Song, Y. Yang, Y. Yang, Z. Huang, and H. T. Shen. Inter-media hashing for large-scale retrieval from heterogeneous data sources. In SIGMOD Conference, pages 785-796, 2013.
    • (2013) SIGMOD Conference , pp. 785-796
    • Song, J.1    Yang, Y.2    Yang, Y.3    Huang, Z.4    Shen, H.T.5
  • 21
    • 84877724347 scopus 로고    scopus 로고
    • Multimodal learning with deep boltzmann machines
    • N. Srivastava and R. Salakhutdinov. Multimodal learning with deep boltzmann machines. In NIPS, pages 2231-2239, 2012.
    • (2012) NIPS , pp. 2231-2239
    • Srivastava, N.1    Salakhutdinov, R.2
  • 22
    • 56449089103 scopus 로고    scopus 로고
    • Extracting and composing robust features with denoising autoencoders
    • P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol. Extracting and composing robust features with denoising autoencoders. In ICML, pages 1096-1103, 2008.
    • (2008) ICML , pp. 1096-1103
    • Vincent, P.1    Larochelle, H.2    Bengio, Y.3    Manzagol, P.-A.4
  • 23
    • 0012951952 scopus 로고    scopus 로고
    • A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces
    • R. Weber, H.-J. Schek, and S. Blott. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In VLDB, pages 194-205, 1998.
    • (1998) VLDB , pp. 194-205
    • Weber, R.1    Schek, H.-J.2    Blott, S.3
  • 24
  • 25
    • 84866037322 scopus 로고    scopus 로고
    • A probabilistic model for multimodal hash function learning
    • Y. Zhen and D.-Y. Yeung. A probabilistic model for multimodal hash function learning. In KDD, pages 940-948, 2012.
    • (2012) KDD , pp. 940-948
    • Zhen, Y.1    Yeung, D.-Y.2
  • 26
    • 84887418815 scopus 로고    scopus 로고
    • Linear cross-modal hashing for efficient multimodal search
    • X. Zhu, Z. Huang, H. T. Shen, and X. Zhao. Linear cross-modal hashing for efficient multimodal search. MM, 2013.
    • (2013) MM
    • Zhu, X.1    Huang, Z.2    Shen, H.T.3    Zhao, X.4
  • 27
    • 38349155191 scopus 로고    scopus 로고
    • Mining semantic correlation of heterogeneous multimedia data for cross-media retrieval
    • Y. Zhuang, Y. Yang, and F. Wu. Mining semantic correlation of heterogeneous multimedia data for cross-media retrieval. IEEE Transactions on Multimedia, 10(2):221-229, 2008.
    • (2008) IEEE Transactions on Multimedia , vol.10 , Issue.2 , pp. 221-229
    • Zhuang, Y.1    Yang, Y.2    Wu, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.