Skip to main content
Have a personal or library account? Click to login
Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses Cover

Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses

Open Access
|Sep 2012

References

  1. Cheeseman, J.M. (2006). Hydrogen peroxide concentrations in leaves under natural conditions,(10): 2435-2444.
  2. Du Buf, H. and Bayer, M. (Eds.) (2002)., World Scientific Publishing, New York, NY/London/Singapore/Hong Kong.
  3. Forgy, E. (1965). Cluster analysis of multivariate data: Efficiency vs. interpretability of classification,: 768-769.
  4. Fukunaga, K. and Hostetler, L. (1975). The estimation of the gradient of a density function, with applications in pattern recognition,(1): 32-40.
  5. Gonzalez, R.C. and Woods, R.E. (2008).3rd Edn., Prentice Hall, Upper Saddle River, NJ.
  6. Hagan, M.T., Demuth, H. B. and Beale, M.H. (2009)., University of Colorado, Denver, CO, Chapter 10, http://www.personeel.unimaas.nl/westra/Education/ANO/10widrow_hoff.pdf
  7. Hecht-Nielsen, R. (1987). Counterpropagation networks,(23): 4979-4984.
  8. Huang, CX-S., Liu, J-H. and Chen, X-J. (2010). Overexpression of PtrABF gene, a bZIP transcription factor isolated from, enhances dehydration and drought tolerance in tobacco via scavenging ROS and modulating expression of stress-responsive genes,: 1-18, paper 230, http://www.biomedcentral.com/1471-2229/10/230.
  9. James, W.C. (1971). An illustrated series of assessment keys for plant diseases, their preparation and usage,(2): 39-65.
  10. Kohonen, T. (1990). The self-organising map,(9): 1464-1479.
  11. Kohonen, T. (2001).3rd Edn., Springer-Verlag, Berlin/ Heidelberg/New York, NY.
  12. Masters, T. (1993), Academic Press Inc., San Diego, CA.
  13. Ong, S., Yeo, N., Lee, K., Venkatesh, Y. and Cao, D. (2002). Segmentation of color images using a two-stage selforganizing network,(4): 279-289.
  14. Osowski, S. (2006)., Warsaw University of Technology Press, Warsaw, (in Polish).
  15. Otsu, N. (1979). A threshold selection method from gray-level histograms,(1): 62-66.
  16. Refaeilzadeh, P., Tang, L. and Liu, H., (2009). Cross-validation,, Springer Publishing Company, New York, NY, pp. 532-538,
  17. Rubner, Y., Puzicha, J., Tomasi, C. and Buhmann J.M. (2001). Empirical evaluation of dissimilarity measures for color and texture,(1): 25-43.
  18. Sanders, J. and Kandrot, E. (2011)., Addison-Wesley, New York, NY/London.
  19. Smith, A.R. (1978). Color gamut transform pairs,(3): 12-19.
  20. Soukupova, J. and Albrechtova, J. (2003). Image analysis-Tool for quantification of histochemical detection of phenolic compounds, lignin and peroxidases in needles of Norway spruce,(4): 595-601.
  21. Tabrizi, P.R., Rezatofighi, S.H. and Yazdanpanah, M.J. (2010). Using PCA and LVQ neural network for automatic recognition of five types of white blood cells,, pp. 5593-5596.
  22. Tang, Q-H., Liu, B-H., Chen, Y-Q., Zhou, X-H. and Ding, JS. (2007). Application of LVQ neural network combined with the genetic algorithm in acoustic seafloor classification,(1): 313-319.
  23. The Mathworks Inc. (2011a). MEX-files guide, http://www.mathworks.com/support/tech-notes/1600/1605.html
  24. The Mathworks Inc. (2011b). Image processing toolbox user’s guide, http://www.mathworks.com//help/toolbox/images/
  25. Thordal-Christensen, H., Zhang, Z., Wei, Y.D. and Collinge, D.B. (1997). Subcellular localization of H2O2 in plants.
  26. H2O2 accumulation in papillae and hypersensitive response during the barley-powdery mildew interaction,
  27. (6): 1187-1194.
  28. Unger, Ch., Kleta, S., Jandl, G. and Tiedemann, A. (2005). Suppression of the defence-related oxidative burst in bean leaf tissue and bean suspension cells by the necrotrophic pathogen,(1): 15-26.
  29. Wijekoon, C.P., Goodwin, P.H. and Hsiang, T. (2008). Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software,(2-3): 94-101.
  30. Widrow, B., Winter, R.G. and Baxter, R.A. (1988). Layered neural nets for pattern recognition,(7): 1109-1118.
DOI: https://doi.org/10.2478/v10006-012-0050-5 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 669 - 684
Published on: Sep 28, 2012
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2012 Jarosław Gocławski, Joanna Sekulska-Nalewajko, Elżbieta Kuźniak, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.