• 沒有找到結果。

第五章 結論與建議

5.2 建議

本研究開發的「監測分析蜜蜂覓食行為之影像系統」已大致建立完成,在硬 體及軟體上皆已達到預期的功能,並且初步運作正常。對此系統未來發展的可能 性,建議如下:

1. 以系統穩定性的角度而言,蜜蜂標籤辨識較大的問題都集中在蜜蜂通道 上,建議未來的研究主要可朝改良通道設計的方向進行。

2. 目前系統所設計之標籤,其大小並非最小,建議未來的研究可將標籤的尺 寸儘量再縮小。

3. 目前的系統外殼,其裝置於蜂箱的時候還不是太方便,建議未來的研究能 夠改善系統外殼的設計,方便使用者拆卸。

參考文獻

1. 台大資工系通訊與多媒體實驗室。2010。Support vector machines 簡介。網址:

http://www.cmlab.csie.ntu.edu.tw/~cyy/learning/tutorials/SVM2.pdf。上網日期:

2010-1-15。

2. 甘凱文。2009。RFID 原理與系統介紹。網址:http://designer.mech.yzu.edu.tw/。

上網日期:2009-10-5。

3. 余林生、孟祥金。2001。義大利蜜蜂胚後發育的觀察與研究。安徽農業大學學 報:28 (2):156-160。

4. 張永仁。1998。昆蟲入門。初版。台北。遠流出版社。

5. Adjare S. O.. 1990. Beekeeping in Africa. 1st ed., Rome: Food and Agriculture Organisation of the United Nations.

6. Ashwin, T. V., and P. S. Sastry. 2002. A font and size-independent OCR system for printed Kannada documents using support vector machines. Sadhana 27(1): 35-58.

7. Avi-Itzhak, H. I., T. A. Diep, and H. Garland. 1995. High Accuracy Optical Character Recognition Using Neural Networks with Centroid Dithering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(2): 218-224.

8. Bradski, G., and A. Kaehler. 2008. Learning OpenCV. 1st ed., New York: O'Reilly Media.

9. Chang C. C., and C. J. Lin. 2001. LIBSVM: a library for support vector machines.

Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm. Accessed 15 January 2010.

10. Check E.. 2006. From hive minds to humans. Nature 443: 893.

11. David C. T., J. S. Kennedy, and A. R. Ludlow. 1983. Finding of a sex pheromone source by gypsy moths released in the field. Nature 303: 804-806.

12. Diagnose-Funk. 2007. The big bee death. Available at:

http://www.diagnose-funk.ch/. Accessed 16 April 2009.

13. Duda R. O., and P. E. Hart. 1972. Use of the hough transformation to detect lines and curves in pictures. Communications of the ACM 15 (1): 11-15.

14. Duda, R., P. Hart, and D. Stork. 2001. Pattern Classification. 2nd ed., 114-117. New York: John Wiley and Sons.

15. Everitt J. H., D. E. Escobar, M. A. Alaniz, M. R. Davis, and J. V. Richerson. 1996.

Using spatial information technologies to map chinese tamarisk (tamarix chinensis) infestations. Weed Science 44 (1): 104-201.

16. Gonzalez, R. C., and R. E. Woods. 2008. Digital Image Processing. 3rd ed. Taipei:

Pearson Education.

17. Guo G., S. Z. Li, and K. L. Chan, 2001. Support vector machines for face recognition. Image and Vision computing 19: 631-638.

18. Hendricks D. E.. 1989. Development of an electronic system for detecting Heliothis sp. moths (Lepidoptera: Noctuidae) and transferring incident information from the field to a computer. Journal of Economic Entomology 82 (2): 672-684.

19. Hobbs S. E., and G. Hodges. 1993. An optical method for automatic classification and recording of a suction trap catch. Bulletin of Entomological Research 83: 47-52.

20. Ikawa, T., H. Okabe, T. Mori, K. Urabe, and T. Ikeshoji. 1994. A method for reconstructing three-dimensional positions of swarming mosquitoes. Journal of Insect Behavior 7(2): 237-248.

21. Juels, A.. 2006. RFID security and privacy: a research survey. IEEE Journal on Selected Areas in Communications 24(1): 381-394.

22. Kim, Y. T.. 1997. Contrast enhancement using brightness preserving bi-histogram equalization. IEEE Transactions on Consumer Electronics 43(1): 1-8.

23. Kimme C., D. Ballard, and J. Sklansky. 1975. Finding circles by an array of accumulators. Communications of the ACM 18 (2): 120-122.

24. Mankin, R. W., R. L. Crocker, K. L. Flanders, and J. P. Shapiro. 1998. Acoustic detection and identification of insects in soil. In “Proceedings of the 16th International Congress of Acoustics and the 135th Annual Meeting of the Acoustical Society of America”, 685–686. P. K. Kuhl and L. A. Crum, eds. Washington, DC:

Acoustical Society of America.

25. Otsu N.. 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9 (1): 62-66.

26. Reynolds, D. R., and J. R. Riley. 2002. Remote-sensing, telemetric and computer-based technologies for investigating insect movement: a survey of existing and potential techniques. Computers and Electronics in Agriculture 35:

271-307.

27. Riley J. R.. 1989. Remote sensing in entomology. Annual Review of Entomology 34:

247-271.

28. Riley J. R.. 1994. Flying insects in the field. In “Video Techniques in Animal Ecology and Behaviour”, ed. S. D. Wratten, 1-15. New York: Chapman & Hall.

29. Riley J. R., D. R. Reynolds, S. Mukhopadhyay, M. R. Ghosh, and T. K. Sarkar.

1995. Long-distance migration of aphids and other small insects in northeast India.

European Journal of Entomology 92: 639-653.

30. Shanthi, N., and K. Duraiswamy. 2009. A novel SVM-based handwritten Tamil character recognition system. Pattern Analysis & Applications 13: 173-180.

31. Streit, S., F. Bock, W. Pirk, and J. Tautz. 2003. Automatic life-long monitoring of

32. Support Vector Machine. 2009. Tutorial on Support Vector Machines and Kernel Methods. Available at: shttp://www.support-vector.net/. Accessed 26 September 2009.

33. Suykens, J. A. K., and J. Vandewalle. 1999. Least squares Support vector machine classifiers. Neural Processing Letters 9(3): 293-300.

34. Trier, Ø. D., A. K. Jain, and T. Taxt. 1996. Feature extraction methods for character recognition - a survey. Pattern Recognition 29 (4): 641-662.

35. Visscher P. K. and T. D. Seeley. 1982. Foraging strategy of honeybee colonies in a temperate deciduous forest. Ecology 63(6): 1790-1801.

36. Walavalkar L., M. Yeasin, A. Narasimhamurthy, and R. Sharma. 2003. Support vector learning for gender classification using audio and visual cues. International Journal of Pattern Recognition and Artificial Intelligence 17 (3): 417-439.

37. Wilson E. O.. 2006. How to make a social insect. Nature 443: 919.

38. Wyatt T. D.. 1997. Methods in studying insect behavior. In “Methods in Ecological and Agricultural Entomology”, ed. D. R. Dent and M. P. Walton, 27-56. New York:

CAB International.

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