|
[1] 李翎竹、林家伃、楊智凱、徐武煥,“智慧農業應用發展現況與 潛在人才需求研析", 農政與農情,337 期,頁 6672 ,2020。 [2] 行政院農委會,農業就業人口統計。[Online]. Available: https: //agrstat.coa.gov.tw/sdweb/public/inquiry/InquireAdvance.aspx, accessed: 20210826. [3] 行政院農委會,單一農產品進出口量值 ─ 按國家別。[Online]. Available: https://agrstat.coa.gov.tw/sdweb/public/trade/tradereport. aspx, accessed: 20210826. [4] 皇基股份有限公司彰化研發中心,“良率預估標準",2021。 [5] A. Paturkar, G. Sen Gupta, and D. Bailey, “Making use of 3D models for plant physiognomic analysis: A review,” Remote Sensing, vol. 13, no. 11, p. 2232, 2021. [6] Z. Li, R. Guo, M. Li, Y. Chen, and G. Li, “A review of computer vi sion technologies for plant phenotyping,” Computers and Electronics in Agriculture, vol. 176, p. 105672, 2020. [7] K. Itakura and F. Hosoi, “Automatic leaf segmentation for estimat ing leaf area and leaf inclination angle in 3D plant images,” Sensors, vol. 18, no. 10, p. 3576, 2018. [8] Y. Chéné, D. Rousseau, P. Lucidarme, J. Bertheloot, V. Caffier, P. Morel, É. Belin, and F. ChapeauBlondeau, “On the use of depth camera for 3D phenotyping of entire plants,” Computers and Electron ics in Agriculture, vol. 82, pp. 122–127, 2012. [9] J. Zou and G. Nagy, “Evaluation of modelbased interactive flower recognition,” Proceedings of the 17th International Conference on Pat tern Recognition, 2004. ICPR 2004., vol. 2, pp. 311–314, Cambridge, UK, August 2326, 2004. [10] Y.A. Chan, M.S. Liao, C.H. Wang, Y.C. Lee, and J.A. Jiang, “Im age repainted method of overlapped leaves for orchid leaf area esti mation,” 2015 9th International Conference on Sensing Technology (ICST), pp. 205–210, Auckland, New Zealand, December 0810, 2015. [11] P. Shi, D. A. Ratkowsky, Y. Li, L. Zhang, S. Lin, and J. Gielis, “A general leaf area geometric formula exists for plants—evidence from the simplified gielis equation,” Forests, vol. 9, no. 11, p. 714, 2018. [12] 陳昶廷,“以機器視覺為基礎之蘭花種苗分級系統",國立中山大 學碩士論文,2019 年 8 月。 [13] P. E. L. Otoya and S. R. P. Gardini, “Realtime noninvasive leaf area measurement method using depth images,” 2020 IEEE ANDESCON, pp. 1–6, 2020. [14] L. Keselman, J. I. Woodfill, A. GrunnetJepsen, and A. Bhowmik, “Intel(r) realsense(tm) stereoscopic depth cameras,” 2017 IEEE Con ference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1267–1276, Honolulu, HI, USA, July 2126, 2017. [15] Intel Corporation. Depth camera d435 intel realsense. [Online]. Avail able: https://www.intelrealsense.com/depthcamerad435i/, accessed: 202106. [16] Y.C. Du, M. Muslikhin, T.H. Hsieh, and M.S. Wang, “Stereo vision based object recognition and manipulation by regions with convolu tional neural network,” Electronics, vol. 9, no. 2, p. 210, 2020. [17] G. Bradski, “The opencv library,” Dr.Dobb’s Journal, vol. 25, no. 11, pp. 120–125, 2000. [18] M. A. Gehan, N. Fahlgren, A. Abbasi, J. C. Berry, S. T. Callen, L. Chavez, A. N. Doust, M. J. Feldman, K. B. Gilbert, J. G. Hodge et al., “Plantcv v2: Image analysis software for highthroughput plant phenotyping,” PeerJ, vol. 5, p. e4088, 2017. [19] P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, İ. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cim rman, I. Henriksen, E. A. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, and SciPy 1.0 Contribu tors, “SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,” Nature Methods, vol. 17, pp. 261–272, 2020. [20] J. Canny, “A computational approach to edge detection,” IEEE Trans actions on pattern analysis and machine intelligence, no. 6, pp. 679– 698, 1986. [21] N. Kanopoulos, N. Vasanthavada, and R. L. Baker, “Design of an image edge detection filter using the sobel operator,” IEEE Journal of solid state circuits, vol. 23, no. 2, pp. 358–367, 1988. [22] H. Heijmans and L. Vincent, “Graph morphology in image analysis,” Mathematical Morphology in Image Processing, vol. 34, pp. 171–203, 1992. [23] S. Narkhede. Understanding confusion matrix. [Online]. Available: https://towardsdatascience.com/understandingconfusionmatrix, ac cessed: 202207. |