Page 102 - NGTU_paper_withoutVideo
P. 102

Modern Geomatics Technologies and Applications

          [7] Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F. J., García-Ferrer, A., & Pérez-
          Porras, F. J. (2018). Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control
          points. International journal of applied earth observation and geoinformation, 72, 1-10.


          [8] Li, S., Peng, M., Wu, C., Feng, X., & Wu, Y., 2015. Optimal selection of GCPs from Global Land Survey 2005 for
          precision geometric correction of Landsat-8 imagery. European Journal of Remote Sensing, 48(1), 303-318.

          [9] Jain, A. K., Murty, M. N., & Flynn, P. J., 1999. Data clustering: a review. ACM computing surveys (CSUR), 31(3), 264-
          323


          [10] Fahad, A., Alshatri, N., Tari, Z., Alamri, A., Khalil, I., Zomaya, A. Y., … & Bouras, A., 2014. A survey of clustering
          algorithms for big data: Taxonomy and empirical analysis. IEEE transactions on emerging topics in computing, 2(3), 267-279

          [11] Maulik, U., & Bandyopadhyay, S., 2000. Genetic algorithm-based clustering technique. Pattern recognition, 33(9), 1455-
          1465.


          [12] Schaeffer, S. E., 2007. Graph clustering. Computer science review, 1(1), 27-64


          [13] Mohammed, N. Z., Ghazi, A., & Mustafa, H. E., 2013. Positional accuracy testing of Google Earth. International Journal
          of Multidisciplinary Sciences and Engineering, 4(6), 6-9.


          [14] Lloyd, Stuart P. "Least squares quantization in PCM." Information Theory, IEEE Transactions on 28.2 (1982): 129-137


          [15] Kaufman, L. and Rousseeuw, P.J. (1987), Clustering by means of Medoids, in Statistical Data Analysis Based on the  –
          Norm and Related Methods, edited by Y. Dodge, North-Holland, 405–41

          [16] Murtagh, Fionn, and Pedro Contreras. "Algorithms for hierarchical clustering: an overview." Wiley Interdisciplinary

          Reviews: Data Mining and Knowledge Discovery 2.1 (2012): 86-97.

          [17] Ester, Martin; Kriegel, Hans-Peter; Sander, Jörg; Xu, Xiaowei (1996). Simoudis, Evangelos; Han, Jiawei; Fayyad, Usama
          M. (eds.). A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second
          International Conference on Knowledge Discovery and Data Mining (KDD-96). AAAI Press. pp. 226–231.

          [18] Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander (1999). OPTICS: Ordering Points To Identify the
          Clustering Structure. ACM SIGMOD international conference on Management of data. ACM Press. pp. 49–60.

          [19] Cheng, Yizong (August 1995). "Mean Shift, Mode Seeking, and Clustering". IEEE Transactions on Pattern Analysis and
          Machine Intelligence. 17 (8): 790–99.

          [20] Dunn, J. C. (1973-01-01). "A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated
          Clusters". Journal of Cybernetics. 3 (3): 32–57.

          [21] Kennedy, J.; Eberhart, R. (1995). "Particle Swarm Optimization". Proceedings of IEEE International Conference on
          Neural Networks. IV. pp. 1942–1948.



                                                                                                              10
   97   98   99   100   101   102   103   104   105   106   107