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Volumn 5303 LNCS, Issue PART 2, 2008, Pages 759-773

Unsupervised structure learning: Hierarchical recursive composition, suspicious coincidence and competitive exclusion

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; HIERARCHICAL CLUSTERING;

EID: 56749102488     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-88688-4_56     Document Type: Conference Paper
Times cited : (56)

References (21)
  • 1
    • 0041940256 scopus 로고    scopus 로고
    • Object class recognition by unsupervised scale-invariant learning
    • Fergus, R., Perona, P., Zisserman, A.: Object class recognition by unsupervised scale-invariant learning. In: CVPR (2), pp. 264-271 (2003)
    • (2003) CVPR , vol.2 , pp. 264-271
    • Fergus, R.1    Perona, P.2    Zisserman, A.3
  • 2
    • 77956172383 scopus 로고    scopus 로고
    • Unsupervised learning of a probabilistic grammar for object detection and parsing
    • Zhu, L., Chen, Y., Yuille, A.L.: Unsupervised learning of a probabilistic grammar for object detection and parsing. In: NIPS, pp. 1617-1624 (2006)
    • (2006) NIPS , pp. 1617-1624
    • Zhu, L.1    Chen, Y.2    Yuille, A.L.3
  • 3
    • 56749103929 scopus 로고    scopus 로고
    • Borenstein, E., Ullman, S.: Class-specific, top-down segmentation. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, 2351, pp. 109-124. Springer, Heidelberg (2002)
    • Borenstein, E., Ullman, S.: Class-specific, top-down segmentation. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2351, pp. 109-124. Springer, Heidelberg (2002)
  • 4
    • 0023846591 scopus 로고
    • Neocognitron: A hierarchical neural network capable of visual pattern recognition
    • Fukushima, K.: Neocognitron: A hierarchical neural network capable of visual pattern recognition. Neural Networks 1, 119-130 (1988)
    • (1988) Neural Networks , vol.1 , pp. 119-130
    • Fukushima, K.1
  • 5
    • 33845568397 scopus 로고    scopus 로고
    • Context and hierarchy in a probabilistic image model
    • Jin, Y., Geman, S.: Context and hierarchy in a probabilistic image model. In: CVPR (2), pp. 2145-2152 (2006)
    • (2006) CVPR , vol.2 , pp. 2145-2152
    • Jin, Y.1    Geman, S.2
  • 6
    • 56749178295 scopus 로고    scopus 로고
    • Chen, Y., Zhu, L., Lin, C., Yuille, A.L., Zhang, H.: Rapid inference on a novel and/or graph for object detection, segmentation and parsing. In: NIPS (2007)
    • Chen, Y., Zhu, L., Lin, C., Yuille, A.L., Zhang, H.: Rapid inference on a novel and/or graph for object detection, segmentation and parsing. In: NIPS (2007)
  • 7
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Computation 18, 1527-1554 (2006)
    • (2006) Neural Computation , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.W.3
  • 8
    • 33745963422 scopus 로고    scopus 로고
    • Feature hierarchies for object classification
    • Epshtein, B., Ullman, S.: Feature hierarchies for object classification. In: ICCV, pp. 220-227 (2005)
    • (2005) ICCV , pp. 220-227
    • Epshtein, B.1    Ullman, S.2
  • 9
    • 24644511277 scopus 로고    scopus 로고
    • Object recognition with features inspired by visual cortex
    • Serre, T., Wolf, L., Poggio, T.: Object recognition with features inspired by visual cortex. In: CVPR (2), pp. 994-1000 (2005)
    • (2005) CVPR , vol.2 , pp. 994-1000
    • Serre, T.1    Wolf, L.2    Poggio, T.3
  • 11
    • 0034981214 scopus 로고    scopus 로고
    • Fleuret, F., Geman, D.: Coarse-to-fine face detection. In: IJCV (2001)
    • Fleuret, F., Geman, D.: Coarse-to-fine face detection. In: IJCV (2001)
  • 13
    • 12844262766 scopus 로고    scopus 로고
    • grabcut: Interactive foreground extraction using iterated graph cuts
    • Rother, C., Kolmogorov, V., Blake, A.: "grabcut": interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23, 309-314 (2004)
    • (2004) ACM Trans. Graph , vol.23 , pp. 309-314
    • Rother, C.1    Kolmogorov, V.2    Blake, A.3
  • 14
    • 84864069589 scopus 로고    scopus 로고
    • Ren, X., Fowlkes, C., Malik, J.: Cue integration for figure/ground labeling. In: NIPS (2005)
    • Ren, X., Fowlkes, C., Malik, J.: Cue integration for figure/ground labeling. In: NIPS (2005)
  • 15
    • 33745827322 scopus 로고    scopus 로고
    • Levin, A., Weiss, Y.: Learning to combine bottom-up and top-down segmentation. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, 3954, pp. 581-594. Springer, Heidelberg (2006)
    • Levin, A., Weiss, Y.: Learning to combine bottom-up and top-down segmentation. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 581-594. Springer, Heidelberg (2006)
  • 18
    • 33845567121 scopus 로고    scopus 로고
    • Shape guided object segmentation
    • Borenstein, E., Malik, J.: Shape guided object segmentation. In: CVPR (1), pp. 969-976 (2006)
    • (2006) CVPR , vol.1 , pp. 969-976
    • Borenstein, E.1    Malik, J.2
  • 19
    • 33745948591 scopus 로고    scopus 로고
    • Locus: Learning object classes with unsupervised segmentation
    • Winn, J.M., Jojic, N.: Locus: Learning object classes with unsupervised segmentation. In: ICCV, pp. 756-763 (2005)
    • (2005) ICCV , pp. 756-763
    • Winn, J.M.1    Jojic, N.2
  • 20
    • 34047174674 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
    • Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. Comput. Vis. Image Underst. 106, 59-70 (2007)
    • (2007) Comput. Vis. Image Underst , vol.106 , pp. 59-70
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 21
    • 33745835982 scopus 로고    scopus 로고
    • Labelme: A database and web-based tool for image annotation
    • Technical Report
    • Russell, B., Torralba, A., Murphy, K., Freeman, W.: Labelme: a database and web-based tool for image annotation. Technical Report (2005)
    • (2005)
    • Russell, B.1    Torralba, A.2    Murphy, K.3    Freeman, W.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.