1. [1] A. Voulodimos, N. Doulamis, A. Doulami, and E. Protopapadakis,
“Deep learning for computer vision: A brief review”, Computational intelligence and
neuroscience, 2018.
2. [2] M. Jahangiri, and S. Ghavami, “Hybrid fuzzy c-means clustering
algorithm and multilayer perceptron for increasing the estimate accuracy of the geochemical
element concentration case study: eastern zone of porphyry copper deposit of Sonajil”,
Iranian Journal of Geology, Vol. 48, No. 48, pp. 0, 2019.
3. [3] M. K. Pakhira, “A fast k-means algorithm using cluster shifting to
produce compact and separate clusters”, Int J Eng, Vol. 28, No. 1, pp. 35-43,
2015.
4. [4] M. Setnes, and U. Kaymak, “Extended fuzzy c-means with volume
prototypes and cluster merging”, In Proceedings of the 6th European Conference on Intelligent
Techniques and Soft Computing (EUFIT’98), 1998, pp. 1360-1364.
5. [5] G. S. Budhi, R. Chiong, and Z. Wang, “Resampling imbalanced data
to detect fake reviews using machine learning classifiers and textual-based features”,
Multimedia Tools and Applications, Vol. 80, No. 9, pp.