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Volumn , Issue , 2009, Pages 1605-1612

Learning invariant features through topographic filter maps

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE RECOGNITION; MAPS; MATHEMATICAL TRANSFORMATIONS; OBJECT RECOGNITION;

EID: 70450177775     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2009.5206545     Document Type: Conference Paper
Times cited : (274)

References (27)
  • 1
    • 84869676680 scopus 로고    scopus 로고
    • http://yann.lecun.com/exdb/mnist/.
  • 5
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
    • L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. In CVPR Workshop, 2004.
    • (2004) CVPR Workshop
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 6
    • 0034222304 scopus 로고    scopus 로고
    • Emergence of phase- and shiftinvariant features by decomposition of natural images into independent feature subspaces
    • Jul.
    • A. Hyvarinen and P. Hoyer. Emergence of phase- and shiftinvariant features by decomposition of natural images into independent feature subspaces. Neural Comput, 12(7):1705- 1720, 2000 Jul.
    • (2000) Neural Comput , vol.12 , Issue.7 , pp. 1705-1720
    • Hyvarinen, A.1    Hoyer, P.2
  • 7
    • 0034920427 scopus 로고    scopus 로고
    • A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images
    • A. Hyvarinen and P. Hoyer. A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images. Vision Research, 41(18):2413- 2423, 2001.
    • (2001) Vision Research , vol.41 , Issue.18 , pp. 2413-2423
    • Hyvarinen, A.1    Hoyer, P.2
  • 8
    • 35649018818 scopus 로고    scopus 로고
    • Complex cell pooling and the statistics of natural images
    • Jun
    • A. Hyvarinen and U. Koster. Complex cell pooling and the statistics of natural images. Network, 18(2):81-100, 2007 Jun.
    • (2007) Network , vol.18 , Issue.2 , pp. 81-100
    • Hyvarinen, A.1    Koster, U.2
  • 9
    • 70049083257 scopus 로고    scopus 로고
    • Fast inference in sparse coding algorithms with applications to object recognition
    • Courant Institute, NYU, CBLL-TR-2008-12-01
    • K. Kavukcuoglu, M. Ranzato, and Y. LeCun. Fast inference in sparse coding algorithms with applications to object recognition. Technical report, CBLL, Courant Institute, NYU, 2008. CBLL-TR-2008-12-01.
    • (2008) Technical Report, CBLL
    • Kavukcuoglu, K.1    Ranzato, M.2    Lecun, Y.3
  • 10
    • 0001380009 scopus 로고    scopus 로고
    • Emergence of invariant-feature detectors in the adaptive-subspace self-organizing map
    • T. Kohonen. Emergence of invariant-feature detectors in the adaptive-subspace self-organizing map. Biol. Cybern., 75:281-291, 1996.
    • (1996) Biol. Cybern. , vol.75 , pp. 281-291
    • Kohonen, T.1
  • 11
    • 33845572523 scopus 로고    scopus 로고
    • Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
    • IEEE, June
    • S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, pages 2169-2178. IEEE, June 2006.
    • (2006) CVPR , pp. 2169-2178
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 12
    • 0032203257 scopus 로고    scopus 로고
    • Gradientbased learning applied to document recognition
    • November
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradientbased learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, November 1998.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • Lecun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 13
    • 5044231640 scopus 로고    scopus 로고
    • Learning methods for generic object recognition with invariance to pose and lighting
    • IEEE Press
    • Y. LeCun, F.-J. Huang, and L. Bottou. Learning methods for generic object recognition with invariance to pose and lighting. In Proceedings of CVPR'04. IEEE Press, 2004.
    • (2004) Proceedings of CVPR'04
    • Lecun, Y.1    Huang, F.-J.2    Bottou, L.3
  • 14
    • 85147175076 scopus 로고    scopus 로고
    • Efficient sparse coding algorithms
    • H. Lee, A. Battle, R. Raina, and A. Ng. Efficient sparse coding algorithms. In NIPS, 2006.
    • (2006) NIPS
    • Lee, H.1    Battle, A.2    Raina, R.3    Ng, A.4
  • 15
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004.
    • (2004) IJCV
    • Lowe, D.1
  • 16
    • 51949103923 scopus 로고    scopus 로고
    • Discriminative learned dictionaries for local image analysis
    • J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman. Discriminative learned dictionaries for local image analysis. In CVPR, 2008.
    • (2008) CVPR
    • Mairal, J.1    Bach, F.2    Ponce, J.3    Sapiro, G.4    Zisserman, A.5
  • 18
    • 33845569574 scopus 로고    scopus 로고
    • Multiclass object recognition with sparse, localized features
    • J. Mutch and D. Lowe. Multiclass object recognition with sparse, localized features. In CVPR, 2006.
    • (2006) CVPR
    • Mutch, J.1    Lowe, D.2
  • 19
    • 0030779611 scopus 로고    scopus 로고
    • Sparse coding with an overcomplete basis set: A strategy employed by v1?
    • B. A. Olshausen and D. J. Field. Sparse coding with an overcomplete basis set: a strategy employed by v1? Vision Research, 37:3311-3325, 1997.
    • (1997) Vision Research , vol.37 , pp. 3311-3325
    • Olshausen, B.A.1    Field, D.J.2
  • 20
    • 33644900506 scopus 로고    scopus 로고
    • Topographic product models applied to natural scene statistics
    • Feb.
    • S. Osindero, M. Welling, and G. E. Hinton. Topographic product models applied to natural scene statistics. Neural Comput, 18(2):381-414, 2006 Feb.
    • (2006) Neural Comput , vol.18 , Issue.2 , pp. 381-414
    • Osindero, S.1    Welling, M.2    Hinton, G.E.3
  • 22
    • 34948870900 scopus 로고    scopus 로고
    • Unsupervised learning of invariant feature hierarchies with applications to object recognition
    • M. Ranzato, F. Huang, Y. Boureau, and Y. LeCun. Unsupervised learning of invariant feature hierarchies with applications to object recognition. In CVPR, 2007.
    • (2007) CVPR
    • Ranzato, M.1    Huang, F.2    Boureau, Y.3    LeCun, Y.4
  • 23
    • 85112276587 scopus 로고    scopus 로고
    • Efficient learning of sparse representations with an energy-based model
    • M. Ranzato, C. Poultney, S. Chopra, and Y. LeCun. Efficient learning of sparse representations with an energy-based model. In NIPS, 2006.
    • (2006) NIPS
    • Ranzato, M.1    Poultney, C.2    Chopra, S.3    LeCun, Y.4
  • 24
    • 51849128608 scopus 로고    scopus 로고
    • Sparse coding via thresholding and local competition in neural circuits
    • C. Rozell, D. Johnson, B. R.G., and B. Olshausen. Sparse coding via thresholding and local competition in neural circuits. Neural Computation, 2008.
    • (2008) Neural Computation
    • Rozell, C.1    Johnson, D.2    Olshausen, B.3
  • 25
    • 24644511277 scopus 로고    scopus 로고
    • Object recognition with features inspired by visual cortex
    • T. Serre, L. Wolf, and T. Poggio. Object recognition with features inspired by visual cortex. In CVPR, 2005.
    • (2005) CVPR
    • Serre, T.1    Wolf, L.2    Poggio, T.3
  • 26
    • 54749092170 scopus 로고    scopus 로고
    • 80 million tiny images: A large dataset for nonparametric object and scene recognition
    • A. Torralba, R. Fergus, and W. T. Freeman. 80 million tiny images: A large dataset for nonparametric object and scene recognition. IEEE PAMI, 30(11):1958-1970, 2008.
    • (2008) IEEE PAMI , vol.30 , Issue.11 , pp. 1958-1970
    • Torralba, A.1    Fergus, R.2    Freeman, W.T.3
  • 27
    • 33746107071 scopus 로고    scopus 로고
    • Model selection and estimation in regression with grouped variables
    • M. Yuan and Y. Lin. Model selection and estimation in regression with grouped variables. Technical report, Univ. of Winsconsin, 2004.
    • (2004) Technical Report, Univ. of Winsconsin
    • Yuan, M.1    Lin, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.