[1] Bartumek J. S.: Fingerprint Image Enhancement, Segmentation and Minutiae Detection, Doctoral Dissertation, Blekinge Institute of Technology (2016) [2] Kulkarni, S.: Fingerprint feature extraction and classification by learning the characteristics of fingerprint patterns. Neural Netw. World 3, 219–226(2011) [3] Oloyede, M.O., Adedoyin, A.O., Adewole, K.S.: Fingerprint biometric authentication for enhancing staff attendance system. Int. J. Appl. Inf. Syst. 5, 19–24(2013) [4] Patil, P., Khachane, A., Purohit, V.: A wireless fingerprint attendance system. Int. J. Secur. Privacy Trust Manag. 5(4), 11–17(2016) [5] Barbadekar, A., Jadhav, S.D., Patil, S.P.: Performance analysis of fingerprint sensors. Vishwakarma Institute of Technology, Pune (2010). https://doi.org/10.1109/ICMEE.2010.5558571 [6] Miguel A.F, Aythami M., Carlos M.T, Jesus B. A.: Combining hand biometric traits for personal identification, In 43rd Annual 2009 International Carnahan Conference on Security Technology, IEEE (2009). https://doi.org/10.1109/CCST.2009.5335547 [7] Chandramohan, J., Nagarajan, R., Kumar, M., Dineshkumar, T., Kannan, G.: Attendance monitoring systems of students based on biometric and GPS tracking syste. Int. J. Adv. Eng. Manage. Sci. 3, 3(2017) [8] Pavol, M., Hambahl, A.: Fingerprint recognition system using artificial neural network as feature extractor: design and performance evaluation. Math. Publ. 67, 117–134(2016) [9] Uhrig R.E.: Introduction to artificial neural networks. In: Proceedings of IECON Annual Conference on IEEE Industrial Electronics (2002). https://doi.org/10.1109/iecon.1995.483329 [10] Bartunek J. S., Nilsson M., Nordberg J., Claesson I.: Neural network based minutiae extraction from skeletonized fingerprints (2006). https://doi.org/10.1109/TENCON.2006.344104 [11] Capplli R.: SFinGe: an approach to synthetic fingerprint generation, in: International Workshop on Biometric Technologies, Calgary, Canada, 147–154(2004) [12] Kumar, N., Kalyan Singh, K.: Wiener filter using digital image restoration. Int. J. Electron. Eng. 3(2), 345–348(2011) [13] Boykov, Y., Vekslers, O., Zabih, R.: Fast approximate energy minimization via Graph Cuts. IEEE PAMI 23(11), 1222–1239(2001) [14] Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions via graph cuts. In: International Conference on Computer Vision, vol. 2, pp. 508–515(2001) [15] Nguyen, T.H., Nguyen, T.L., Dreglea, A.I.: Machine learning algorithms application to road defects classification. Intell. Decis. Technol. 59–66, 12(2018) [16] Nguyen, T.H., Nguyen, T.L., Dreglea, A.I.: Robust approach to detection of bubbles based on images analysis. Int. J. Artif. Intell. 16, 167–177(2018) [17] Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Singularity and Core Detection” Extract from “Handbook of Fingerprint Recognition. Springer, New York (2003) [18] Jain, A.K., Flynn, P., Ross, A.A.: Handbook of Biometrics. Springer, Berlin (2008) [19] Maas, A.L., Hannun, A.Y., Ng, A.Y.: Rectifier nonlinearities improve neural network acoustic models. In: Proceedings of icml, vol. 30, no. 1(2013) [20] Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhut dinov, R.: A simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958(2014) [21] Vasseur, J.-P., Dunkels, A.: in Interconnecting Smart Objects with IP (2010). https://doi.org/10.1016/ C2009-0-20667-2 [22] Zweig, M.H., Campbell, G.: Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin. Chem. 39, 561–577(1993) [23] Nguyen, T.H., Nguyen, T.L.: ROC curve analysis for classification of road defects. BRAIN Broad Res. Artif. Intell. Neurosci. 10(2), 65–73(2019) [24] Breiman, L.: Random forests. Mach. Learn. 45, 5–32(2001). https://doi.org/10.1023/A:1010933404324 [25] Awad, M., Khanna, R.: Support vector machines for classification, efficient learning machines, pp 39–66(2015) [26] Liu, Y.: Mean square error of survey estimates, encyclopedia of quality of life and well-being research, 2014, ISBN: 978-94-007-0752-8 [27] Thomas, J., PinarKaragoz, J., BazeerAhamed, B., Vasant, P.: Deep learning techniques and optimization strategies in big data analytics. IGI Global 13, 1–355(2020). https://doi.org/10.4018/978-1-7998-1192-3 [28] Vasant, P., Zelinka, I.: Gerhard-Wilhelm Weber, Intelligent Computing& Optimization, 2019,Volume 866, ISBN : 978-3-030-00978-6, https://www.springer.com/gp/book/9783030009786 [29] Vasant, P., Zelinka, I.: Gerhard-Wilhelm Weber, Intelligent Computing & Optimization, Proceedings of the 2nd International Conference on Intelligent Computing and Optimization 2019, https://www.springer.com/gp/book/9783030335847 |