메뉴 건너뛰기




Volumn 6, Issue , 2012, Pages

Learning and disrupting invariance in visual recognition with a temporal association rule

Author keywords

Cortical models; Inferotemporal cortex; Invariance; Object recognition; Trace rule; Vision; Visual development

Indexed keywords

ASSOCIATION RULES; INVARIANCE; VISION;

EID: 84964358644     PISSN: None     EISSN: 16625188     Source Type: Journal    
DOI: 10.3389/fncom.2012.00037     Document Type: Article
Times cited : (27)

References (22)
  • 1
    • 27744553420 scopus 로고    scopus 로고
    • ‘Breaking’ position-invariant object recognition
    • Cox, D., Meier, P., Oertelt, N., and DiCarlo, J. J. (2005). ‘Breaking’ position-invariant object recognition. Nat. Neurosci. 8, 1145–1147.
    • (2005) Nat. Neurosci. , vol.8 , pp. 1145-1147
    • Cox, D.1    Meier, P.2    Oertelt, N.3    Dicarlo, J.J.4
  • 2
    • 23044508992 scopus 로고    scopus 로고
    • Learning viewpoint invariant object representations using a temporal coherence principle
    • Einhauser, W., Hipp, J., Eggert, J., Korner, E., and Konig, P. (2005). Learning viewpoint invariant object representations using a temporal coherence principle. Biol. Cybern. 93, 79–90.
    • (2005) Biol. Cybern. , vol.93 , pp. 79-90
    • Einhauser, W.1    Hipp, J.2    Eggert, J.3    Korner, E.4    Konig, P.5
  • 3
    • 0000188120 scopus 로고
    • Learning invariance from transformation sequences
    • Foldiak, P. (1991). Learning invariance from transformation sequences. Neural Comput. 3, 194–200.
    • (1991) Neural Comput , vol.3 , pp. 194-200
    • Foldiak, P.1
  • 4
    • 34548412214 scopus 로고    scopus 로고
    • Slowness and sparseness lead to place, head-direction, and spatial-view cells
    • Franzius, M., Sprekeler, H., and Wiskott, L. (2007). Slowness and sparseness lead to place, head-direction, and spatial-view cells. PLoS Comput. Biol. 3:e166. doi: 10.1371/journal.pcbi.0030166
    • (2007) Plos Comput. Biol. , vol.3
    • Franzius, M.1    Sprekeler, H.2    Wiskott, L.3
  • 5
    • 0019152630 scopus 로고
    • Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
    • Fukushima, K. (1980). Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 36, 193–201.
    • (1980) Biol. Cybern. , vol.36 , pp. 193-201
    • Fukushima, K.1
  • 6
    • 0030979035 scopus 로고    scopus 로고
    • Becoming a “greeble” expert: Exploring mechanisms for face recognition
    • Gauthier, I., and Tarr, M. (1997). Becoming a “greeble” expert: exploring mechanisms for face recognition. Vision Res. 37, 1673–1682.
    • (1997) Vision Res , vol.37 , pp. 1673-1682
    • Gauthier, I.1    Tarr, M.2
  • 7
    • 33645410496 scopus 로고
    • Receptive fields, binocular interaction and functional architecture in the cats visual cortex
    • Hubel, D. H., and Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cats visual cortex. J. Physiol. 160, 106–154.
    • (1962) J. Physiol. , vol.160 , pp. 106-154
    • Hubel, D.H.1    Wiesel, T.N.2
  • 10
    • 51749124671 scopus 로고    scopus 로고
    • Unsupervised natural experience rapidly alters invariant object representation in visual cortex
    • Li, N., and DiCarlo, J. J. (2008). Unsupervised natural experience rapidly alters invariant object representation in visual cortex. Science 321, 1502–1507.
    • (2008) Science , vol.321 , pp. 1502-1507
    • Li, N.1    Dicarlo, J.J.2
  • 11
    • 77957009642 scopus 로고    scopus 로고
    • Unsupervised natural visual experience rapidly reshapes size-invariant object representation in inferior temporal cortex
    • Li, N., and DiCarlo, J. J. (2010). Unsupervised natural visual experience rapidly reshapes size-invariant object representation in inferior temporal cortex. Neuron 67, 1062–1075.
    • (2010) Neuron , vol.67 , pp. 1062-1075
    • Li, N.1    Dicarlo, J.J.2
  • 13
    • 33847275584 scopus 로고    scopus 로고
    • Unsupervised learning of visual features through spike timing dependent plasticity
    • Masquelier, T., and Thorpe, S. J. (2007). Unsupervised learning of visual features through spike timing dependent plasticity. PLoS Comput. Biol. 3:e31. doi: 10.1371/journal.pcbi.0030031
    • (2007) Plos Comput. Biol. , vol.3
    • Masquelier, T.1    Thorpe, S.J.2
  • 14
    • 0033316361 scopus 로고    scopus 로고
    • Hierarchical models of object recognition in cortex
    • Riesenhuber, M., and Poggio, T. (1999). Hierarchical models of object recognition in cortex. Nat. Neurosci. 2, 1019–1025.
    • (1999) Nat. Neurosci. , vol.2 , pp. 1019-1025
    • Riesenhuber, M.1    Poggio, T.2
  • 16
    • 18144401295 scopus 로고    scopus 로고
    • Learning viewpoint invariant perceptual representations from cluttered images
    • Spratling, M. (2005). Learning viewpoint invariant perceptual representations from cluttered images. IEEE Trans. Pattern Anal. Mach. Intell. 27, 753–761.
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , pp. 753-761
    • Spratling, M.1
  • 17
    • 0029069557 scopus 로고
    • View-based models of 3D object recognition: Invariance to imaging transformations
    • Vetter, T., Hurlbert, A., and Poggio, T. (1995). View-based models of 3D object recognition: invariance to imaging transformations. Cereb. Cortex 3, 261–269.
    • (1995) Cereb. Cortex , vol.3 , pp. 261-269
    • Vetter, T.1    Hurlbert, A.2    Poggio, T.3
  • 18
    • 85027511045 scopus 로고    scopus 로고
    • Learning illumination-and orientation-invariant representations of objects through temporal association
    • Wallis, G., Backus, B. T., Langer, M., Huebner, G., and Bulthoff, H. (2009). Learning illumination-and orientation-invariant representations of objects through temporal association. J. Vis. 96, 1–8.
    • (2009) J. Vis , vol.96 , pp. 1-8
    • Wallis, G.1    Backus, B.T.2    Langer, M.3    Huebner, G.4    Bulthoff, H.5
  • 19
    • 0035836774 scopus 로고    scopus 로고
    • Effects of temporal association on recognition memory
    • Wallis, G., and Bulthoff, H. (2001). Effects of temporal association on recognition memory. Proc. Natl. Acad. Sci. U.S.A. 98, 4800–4804.
    • (2001) Proc. Natl. Acad. Sci. U.S.A. , vol.98 , pp. 4800-4804
    • Wallis, G.1    Bulthoff, H.2
  • 20
    • 0031040957 scopus 로고    scopus 로고
    • Invariant face and object recognition in the visual system
    • Wallis, G., and Rolls, E. T. (1997). Invariant face and object recognition in the visual system. Prog. Neurobiol. 51, 167–194.
    • (1997) Prog. Neurobiol. , vol.51 , pp. 167-194
    • Wallis, G.1    Rolls, E.T.2
  • 21
    • 0036546660 scopus 로고    scopus 로고
    • Slow feature analysis: Unsupervised learning of invariances
    • Wiskott, L., and Sejnowski, T. J. (2002). Slow feature analysis: unsupervised learning of invariances. Neural Comput. 14, 715–770.
    • (2002) Neural Comput , vol.14 , pp. 715-770
    • Wiskott, L.1    Sejnowski, T.J.2
  • 22
    • 33646748872 scopus 로고    scopus 로고
    • A model of the ventral visual system based on temporal stability and local memory
    • Wyss, R., Konig, P., and Verschure, P. (2006). A model of the ventral visual system based on temporal stability and local memory. PLoS Biol. 4:e120. doi: 10.1371/journal.pbio.0040120
    • (2006) Plos Biol. , vol.4
    • Wyss, R.1    Konig, P.2    Verschure, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.