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Volumn , Issue , 2009, Pages 1069-1077

Occlusive components analysis

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; COMPUTER VISION; LEARNING ALGORITHMS; MAXIMUM LIKELIHOOD; MAXIMUM PRINCIPLE;

EID: 84858716136     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (16)

References (20)
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  • 2
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  • 4
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    • Greedy learning of multiple objects in images using robust statistics and factorial learning
    • C. K. I. Williams and M. K. Titsias. Greedy learning of multiple objects in images using robust statistics and factorial learning. Neural Computation, 16(5):1039-1062, 2004.
    • (2004) Neural Computation , vol.16 , Issue.5 , pp. 1039-1062
    • Williams, C.K.I.1    Titsias, M.K.2
  • 5
    • 11844251371 scopus 로고    scopus 로고
    • Restoring partly occluded patterns: A neural network model
    • K. Fukushima. Restoring partly occluded patterns: a neural network model. Neural Networks, 18(1):33-43, 2005.
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    • Fukushima, K.1
  • 6
    • 33646798105 scopus 로고    scopus 로고
    • Analysis of cluttered scenes using an elastic matching approach for stereo images
    • C. Eckes, J. Triesch, and C. von der Malsburg. Analysis of cluttered scenes using an elastic matching approach for stereo images. Neural Computation, 18(6):1441-1471, 2006.
    • (2006) Neural Computation , vol.18 , Issue.6 , pp. 1441-1471
    • Eckes, C.1    Triesch, J.2    Von Der Malsburg, C.3
  • 7
    • 0002788893 scopus 로고    scopus 로고
    • A view of the EM algorithm that justifies incremental, sparse, and other variants
    • M. I. Jordan, editor Kluwer
    • R. M. Neal and G. E. Hinton. A view of the EM algorithm that justifies incremental, sparse, and other variants. In M. I. Jordan, editor, Learning in Graphical Models. Kluwer, 1998.
    • (1998) Learning in Graphical Models
    • Neal, R.M.1    Hinton, G.E.2
  • 8
    • 46749096794 scopus 로고    scopus 로고
    • Maximal causes for non-linear component extraction
    • J. Lücke and M. Sahani. Maximal causes for non-linear component extraction. Journal of Machine Learning Research, 9:1227 - 1267, 2008.
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 1227-1267
    • Lücke, J.1    Sahani, M.2
  • 9
    • 0032029288 scopus 로고    scopus 로고
    • Deterministic annealing EM algorithm
    • N. Ueda and R. Nakano. Deterministic annealing EM algorithm. Neural Networks, 11(2):271-282, 1998.
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    • Ueda, N.1    Nakano, R.2
  • 11
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    • Forming sparse representations by local anti-hebbian learning
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  • 12
    • 33646697510 scopus 로고    scopus 로고
    • Learning image components for object recognition
    • M. W. Spratling. Learning image components for object recognition. Journal of Machine Learning Research, 7:793 - 815, 2006.
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    • Spratling, M.W.1
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  • 14
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
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    • Learning optimized features for hierarchical models of invariant object recognition
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  • 18
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  • 19
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    • Distinctive image features from scale-invariant keypoints
    • D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110, 2004.
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    • Lowe, D.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.