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Volumn 3, Issue , 2010, Pages 2267-2281

Adaboost and support vector machine classifiers for automatic weed control: Canola and wheat

Author keywords

Adaboost; Automatic weed control; Canola; Machine vision; Precision agriculture; Wheat

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURE; ALGORITHMS; BAYESIAN NETWORKS; CLASSIFIERS; COMPUTER VISION; ENGINEERS; FEATURE EXTRACTION; PLANTS (BOTANY); RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES; VECTORS; WEED CONTROL;

EID: 78649709558     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (7)

References (24)
  • 1
    • 36948999941 scopus 로고    scopus 로고
    • Irvine, CA: University of California, Department of Information and Computer Science
    • Asuncion, A. and D. J. Newman. 2007. UCI Machine Learning Repository [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.
    • (2007) UCI Machine Learning Repository
    • Asuncion, A.1    Newman, D.J.2
  • 2
    • 76549106519 scopus 로고    scopus 로고
    • Visual detection of blemishes in potatoes using minimalist boosted classifiers
    • Barnes, M., T. Duckett, G. Cielniak, G. Stround, and G. Harper. 2010. Visual detection of blemishes in potatoes using minimalist boosted classifiers. Journal of Food Engineering 98(3): 339-346.
    • (2010) Journal of Food Engineering , vol.98 , Issue.3 , pp. 339-346
    • Barnes, M.1    Duckett, T.2    Cielniak, G.3    Stround, G.4    Harper, G.5
  • 3
    • 4544345162 scopus 로고    scopus 로고
    • Pizza sauce spread classification using color vision and support vector machines
    • Du, C. J., and D. W. Sun. 2005. Pizza sauce spread classification using color vision and support vector machines. Journal of Food Engineering 66: 137-145.
    • (2005) Journal of Food Engineering , vol.66 , pp. 137-145
    • Du, C.J.1    Sun, D.W.2
  • 5
    • 0033281701 scopus 로고    scopus 로고
    • Improved boosting algorithms using confidence-rated predictions
    • Freund, Y., and R. E. Schapire. 1999a. Improved boosting algorithms using confidence-rated predictions. Machine Learning 37(3): 297-336.
    • (1999) Machine Learning , vol.37 , Issue.3 , pp. 297-336
    • Freund, Y.1    Schapire, R.E.2
  • 7
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • Friedman, J., T. Hastie, and R. Tibshirani. 2000. Additive logistic regression: A statistical view of boosting. The Annals of Statistics 28(2): 337-374.
    • (2000) The Annals of Statistics , vol.28 , Issue.2 , pp. 337-374
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 8
    • 33947168099 scopus 로고    scopus 로고
    • Crop verses weed recognition with artificial neural networks
    • St. Joseph, Mich.:ASAE
    • Gliever, C., and D. C. Slaughter. 2001. Crop verses weed recognition with artificial neural networks. ASAE Meeting Paper No. 01-3104. St. Joseph, Mich.:ASAE.
    • (2001) ASAE Meeting Paper No. 01-3104
    • Gliever, C.1    Slaughter, D.C.2
  • 11
    • 55449125185 scopus 로고    scopus 로고
    • Support Vector Machines and Kernels for Computational Biology
    • Available at Accessed on Accessed on 30 April 2010
    • Hur, A. B., C. S. Ong, S. Sonnenburg, B. Scholkopf, and G. Rätsch. 2008. Support Vector Machines and Kernels for Computational Biology. PLoS Computational Biology. Available at http://www.ncbi.nlm.nih.gov/pmc/articles/ PMC2547983/pdf/pcbi.1000173.pdf. Accessed on Accessed on 30 April 2010.
    • (2008) PLoS Computational Biology
    • Hur, A.B.1    Ong, C.S.2    Sonnenburg, S.3    Scholkopf, B.4    Rätsch, G.5
  • 12
    • 32644445913 scopus 로고    scopus 로고
    • Application of support vector machine technology for weed and nitrogen stress detection in corn
    • DOI 10.1016/j.compag.2005.12.001, PII S0168169906000111
    • Karimi, Y., S. O. Prasher, R.M. Patel, and S.H. Kim. 2006. Application of support vector machine technology for weed and nitrogen stress detection in corn. Computers and Electronics in Agriculture 51(1-2): 99-109. (Pubitemid 43242936)
    • (2006) Computers and Electronics in Agriculture , vol.51 , Issue.1-2 , pp. 99-109
    • Karimi, Y.1    Prasher, S.O.2    Patel, R.M.3    Kim, S.H.4
  • 14
    • 78649708972 scopus 로고    scopus 로고
    • Local adaptive thresholding and adaboost classifier for automated x-ray imaging system for pecan defect detection
    • Stillwater, OK: Food and Agricultural Products Center, Oklahoma State University
    • Mathanker, S. K., P. R. Weckler, T. Bowser, N. Wang, N. O. Maness, G. Fan, and M. Stone. 2010. Local adaptive thresholding and adaboost classifier for automated x-ray imaging system for pecan defect detection. FAPC/IFT-OK Research Symposium, Stillwater, OK: Food and Agricultural Products Center, Oklahoma State University.
    • (2010) FAPC/IFT-OK Research Symposium
    • Mathanker, S.K.1    Weckler, P.R.2    Bowser, T.3    Wang, N.4    Maness, N.O.5    Fan, G.6    Stone, M.7
  • 15
    • 63149134463 scopus 로고    scopus 로고
    • Canola - Weed identification for machine vision based patch spraying
    • St. Joseph, Mich.: ASABE
    • Mathanker, S. K., P. R. Weckler, and R. K. Taylor. 2008. Canola - weed identification for machine vision based patch spraying. ASABE Meeting Paper No. 085134. St. Joseph, Mich.: ASABE.
    • (2008) ASABE Meeting Paper No. 085134
    • Mathanker, S.K.1    Weckler, P.R.2    Taylor, R.K.3
  • 17
    • 35248862907 scopus 로고    scopus 로고
    • An introduction to boosting and leveraging
    • Berlin: Springer
    • Meir, R. and G. Rätsch. 2003. An introduction to boosting and leveraging: In Advanced Lectures on Machine Learning 118-183. Berlin: Springer.
    • (2003) Advanced Lectures on Machine Learning , pp. 118-183
    • Meir, R.1    Rätsch, G.2
  • 21
    • 78149343462 scopus 로고    scopus 로고
    • A computer vision approach for weeds identification through support vector machines
    • In Press, Corrected Proof
    • Tellaeche, A., G. Pajares, X. P. Burgos-Artizzu and A. Ribeiro. 2010. A computer vision approach for weeds identification through support vector machines.Applied Soft Computing In Press, Corrected Proof.
    • (2010) Applied Soft Computing
    • Tellaeche, A.1    Pajares, G.2    Burgos-Artizzu, X.P.3    Ribeiro, A.4
  • 24
    • 76549131104 scopus 로고    scopus 로고
    • Available at: Accessed on 2 October 2009
    • Vezhnevets, A. 2006. GML AdaBoost MATLAB Toolbox. Available at: 〈http://research.graphicon.ru〉. Accessed on 2 October 2009.
    • (2006) GML AdaBoost MATLAB Toolbox
    • Vezhnevets, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.