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Volumn 40, Issue 24, 2000, Pages 3427-3434

A Bayesian model for the measurement of visual velocity

Author keywords

Bayesian; Model; Motion; Optimal; Velocity

Indexed keywords

ARTICLE; BAYES THEOREM; BRAIN; CONTRAST; FILTER; MATHEMATICAL MODEL; MEASUREMENT; MOTION; PERCEPTION; PRIORITY JOURNAL; PSYCHOPHYSICS; VELOCITY; VISION;

EID: 0033771942     PISSN: 00426989     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0042-6989(00)00176-0     Document Type: Article
Times cited : (38)

References (33)
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  • 4
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  • 5
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    • De Valois, R. L., & De Valois, K. K. (1990). Spatial vision. Oxford: Oxford Science Publications.
  • 14
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    • Heeger, D. J. (1991). Non linear model of neural responses in cat visual cortex. In M. Landy & J. A. Movshon, Computational models of visual processing. (pp. 119-133). Cambridge, MA: MIT Press.
  • 21
    • 85002448726 scopus 로고    scopus 로고
    • Smith, J., & Grzywacz, N. M. (1993). A local model for transparent motions based on spatio-temporal filtering. In: F. Eeckman & J. Bower, Computation and neural systems 1992. Dordrecht: Kluwer Academic Press.
  • 26
    • 85002303735 scopus 로고    scopus 로고
    • Ullman, S., & Yuille, A. (1989). Rigidity and smoothness of motion. In: S. Ullman & W. Richards, Image understanding. Norwood, NJ: Ablex Publishing Corporation.
  • 28
    • 85002108875 scopus 로고    scopus 로고
    • Watson, A. B. (1986). Temporal sensitivity. In: K. R. Boff, L. Kaufman, & J. P. Thomas, Handbook of perception and human performance. (vol. I). New York: Wiley.
  • 30
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    • Weiss, Y., & Adelson, E. (1998). Slow and smooth: a Bayesian theory for the combination of local motion signals in human vision (AI Memo No. 1624). Massachusetts Institute of Technology.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.