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Volumn FS-13-02, Issue , 2013, Pages 102-106

Sports video classification from multimodal information using deep neural networks

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; SPORTS;

EID: 84898846309     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (18)
  • 1
    • 84969135721 scopus 로고    scopus 로고
    • k-means++: The advantages of careful seeding
    • Arthur, D., Vassilvitskii, S., k-means++: The advantages of careful seeding, SODA 2007
    • (2007) SODA
    • Arthur, D.1    Vassilvitskii, S.2
  • 5
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • Hinton, G.E., Salakhutdinov, R.R, Reducing the dimensionality of data with neural networks, Science 2006.
    • (2006) Science
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 9
    • 80052874098 scopus 로고    scopus 로고
    • Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis
    • Le, Q.V., Zou, W.Y., Yeung S., Ng A.Y., Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis, CVPR, 2011
    • (2011) CVPR
    • Le, Q.V.1    Zou, W.Y.2    Yeung, S.3    Ng, A.Y.4
  • 10
    • 85161980001 scopus 로고    scopus 로고
    • Sparse deep belief net model for visual area V2
    • Lee, H., Ekanadham, C., Ng, A. Y., Sparse deep belief net model for visual area V2, NIPS 2008.
    • (2008) NIPS
    • Lee, H.1    Ekanadham, C.2    Ng, A.Y.3
  • 11
    • 71149119164 scopus 로고    scopus 로고
    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • Lee, H., Grosse, R., Ranganathan, R., and Ng, A.Y., Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, ICML 2009.
    • (2009) ICML
    • Lee, H.1    Grosse, R.2    Ranganathan, R.3    Ng, A.Y.4
  • 12
    • 84863380535 scopus 로고    scopus 로고
    • Unsupervised feature learning for audio classification using convolutional Deep Belief Networks
    • Lee, H., Largman, Y.,Pham, P., Ng, A.Y., - Unsupervised feature learning for audio classification using convolutional Deep Belief Networks, NIPS 2009.
    • (2009) NIPS
    • Lee, H.1    Largman, Y.2    Pham, P.3    Ng, A.Y.4
  • 13
    • 70349675925 scopus 로고    scopus 로고
    • Fast approximate nearest neighbors with automatic algorithm configuration
    • Muja, M., Lowe, D.G., Fast approximate nearest neighbors with automatic algorithm configuration, ViSAPP 2009
    • (2009) ViSAPP
    • Muja, M.1    Lowe, D.G.2
  • 15
    • 51949106645 scopus 로고    scopus 로고
    • Self-taught learning: Transfer learning from unlabeled data
    • Raina, R., Battle, A., Lee, H., Packer, V., Ng, A.Y., Self-taught learning: Transfer learning from unlabeled data, ICML 2007.
    • (2007) ICML
    • Raina, R.1    Battle, A.2    Lee, H.3    Packer, V.4    Ng, A.Y.5
  • 16
    • 84863049755 scopus 로고    scopus 로고
    • Efficient learning of sparse, distributed, convolutional feature representations for object recognition
    • Sohn, K., Jung, D.Y., Lee, H., Hero, A.O., Efficient learning of sparse, distributed, convolutional feature representations for object recognition, ICCV 2011.
    • (2011) ICCV
    • Sohn, K.1    Jung, D.Y.2    Lee, H.3    Hero, A.O.4
  • 17
    • 84877724347 scopus 로고    scopus 로고
    • Multimodal Learning with Deep Boltzmann Machines
    • Srivastava, N., Salakhutdinov, R., Multimodal Learning with Deep Boltzmann Machines, NIPS 2012
    • (2012) NIPS
    • Srivastava, N.1    Salakhutdinov, R.2
  • 18
    • 84898897856 scopus 로고    scopus 로고
    • ufldl.stanford.edu - Deep Learning Tutorial
    • ufldl.stanford.edu - Deep Learning Tutorial


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.