메뉴 건너뛰기




Volumn , Issue , 2013, Pages 60-65

Learning computationally efficient approximations of complex image segmentation metrics

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; GEOMETRY; IMAGE ANALYSIS; REGRESSION ANALYSIS;

EID: 84896358164     PISSN: 18455921     EISSN: 18492266     Source Type: Conference Proceeding    
DOI: 10.1109/ispa.2013.6703715     Document Type: Conference Paper
Times cited : (5)

References (20)
  • 1
    • 84879983002 scopus 로고    scopus 로고
    • Survey of contemporary trends in color image segmentation
    • S. R. Vantaram and E. Saber, "Survey of contemporary trends in color image segmentation," J. Electron. Imag., vol. 21, no. 4, pp. 1-28, 2012.
    • (2012) J. Electron. Imag. , vol.21 , Issue.4 , pp. 1-28
    • Vantaram, S.R.1    Saber, E.2
  • 2
    • 0034850577 scopus 로고    scopus 로고
    • A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring Ecological Statistics
    • M. Martin, C. Fowlkes, D. Tal, and J. Malik, "A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics," in Proc. 8th Int. Conf. on Computer Vision, vol. 2, 2001, pp. 416-423.
    • (2001) Proc. 8th Int. Conf. on Computer Vision , vol.2 , pp. 416-423
    • Martin, M.1    Fowlkes, C.2    Tal, D.3    Malik, J.4
  • 4
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering methods
    • W. M. Rand, "Objective Criteria for the Evaluation of Clustering Methods," J. Am. Statist. Assoc., vol. 66, no. 336, pp. 846-850, 1971.
    • (1971) J. Am. Statist. Assoc. , vol.66 , Issue.336 , pp. 846-850
    • Rand, W.M.1
  • 5
    • 85116222439 scopus 로고
    • A modified hausdorff distance for object matching
    • M. P. Dubuisson and A. K. Jain, "A Modified Hausdorff Distance for Object Matching," in IAPR, no. 1, 1994, pp. 566-568.
    • (1994) IAPR , Issue.1 , pp. 566-568
    • Dubuisson, M.P.1    Jain, A.K.2
  • 6
    • 38149137371 scopus 로고    scopus 로고
    • A quantitative object-Level metric for segmentation performance and its application to cell nuclei
    • L. E. Boucheron, N. R. Harvey, and B. S. Manjunath, "A Quantitative Object-Level Metric for Segmentation Performance and Its Application to Cell Nuclei," in Adv. in Vis. Comput., 2007, vol. 4841, pp. 208-219.
    • (2007) Adv. in Vis. Comput. , vol.4841 , pp. 208-219
    • Boucheron, L.E.1    Harvey, N.R.2    Manjunath, B.S.3
  • 9
    • 84055171364 scopus 로고    scopus 로고
    • A linear time algorithm of computing hausdorff distance for content-based image analysis
    • M. J. Hossain, K. Ahn, and O. Chae, "A Linear Time Algorithm of Computing Hausdorff Distance for Content-based Image Analysis," Circ. Syst. Signal Process., vol. 31, no. 1, pp. 389-399, 2012.
    • (2012) Circ. Syst. Signal Process. , vol.31 , Issue.1 , pp. 389-399
    • Hossain, M.J.1    Ahn, K.2    Chae, O.3
  • 13
    • 84868329144 scopus 로고    scopus 로고
    • Rosette tracker an open source image analysis tool for automatic quantification of genotype effects
    • J. De Vylder, F. Vandenbussche, Y. Hu, W. Philips, and D. Van Der Straeten, "Rosette tracker: an open source image analysis tool for automatic quantification of genotype effects," Plant physiology, vol. 160, no. 3, pp. 1149-1159, 2012.
    • (2012) Plant Physiology , vol.160 , Issue.3 , pp. 1149-1159
    • De Vylder, J.1    Vandenbussche, F.2    Hu, Y.3    Philips, W.4    Straeten Der D.Van5
  • 14
    • 9444274777 scopus 로고    scopus 로고
    • Comparing clusterings by the variation of information
    • M. Meila, "Comparing Clusterings by the Variation of Information," in Computational Learning Theory, vol. 2777, 2003, pp. 173-187.
    • (2003) Computational Learning Theory , vol.2777 , pp. 173-187
    • Meila, M.1
  • 15
    • 67349252469 scopus 로고    scopus 로고
    • An evaluation metric for image segmentation of multiple objects
    • M. Polak, H. Zhang, and M. Pi, "An evaluation metric for image segmentation of multiple objects," Image and Vision Computing, vol. 27, no. 8, pp. 1223-1227, 2009.
    • (2009) Image and Vision Computing , vol.27 , Issue.8 , pp. 1223-1227
    • Polak, M.1    Zhang, H.2    Pi, M.3
  • 17
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman, "Random Forests," Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 18
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • R. Tibshirani, "Regression Shrinkage and Selection via the Lasso," J. R. Stat. Soc. Series B Stat. Methodol., vol. 58, no. 1, pp. 267-288, 1996.
    • (1996) J. R. Stat. Soc. Series B Stat. Methodol. , vol.58 , Issue.1 , pp. 267-288
    • Tibshirani, R.1
  • 19
    • 57349174008 scopus 로고    scopus 로고
    • Enhancing sparsity by reweighted l1 minimization
    • E. Candes, M. B. Wakin, and S. Boyd, "Enhancing sparsity by reweighted l1 minimization," J. Fourier Analysis and App., vol. 14, no. 5, pp. 877-905, 2008.
    • (2008) J. Fourier Analysis and App. , vol.14 , Issue.5 , pp. 877-905
    • Candes, E.1    Wakin, M.B.2    Boyd, S.3
  • 20
    • 79955830859 scopus 로고    scopus 로고
    • HTPheno an image analysis pipeline for high-throughput plant phenotyping
    • A. Hartmann, T. Czauderna, R. Hoffmann, N. Stein, and F. Schreiber, "HTPheno: An image analysis pipeline for high-throughput plant phenotyping," BMC Bioinformatics, vol. 12, no. 1, p. 148, 2011.
    • (2011) BMC Bioinformatics , vol.12 , Issue.1 , pp. 148
    • Hartmann, A.1    Czauderna, T.2    Hoffmann, R.3    Stein, N.4    Schreiber, F.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.