Evrişimsel Sinir Ağı Temelli Yüz Tanıma Yöntemleri ile Robot Resim Oluşturma Uygulaması

Create a Sketch Application with Convolutional Neural Network Based Face Recognition Methods

Anahtar Kelimeler:

Aile yüz veri seti, Evrişimsel sinir ağı, Robot resim oluşturma, Yüz tanıma

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[1] Anonim. (2020, 9 Nisan). Makine öğrenmesi. [Online]. Erişim: http://www.prowmes.com/blog/makine-ogrenmesi/.
[2] A. Varol ve B. Cebe, “Algorithms of face recognition,” 5th International Computer ve Instructional Technologies Symposium, Elazığ, Türkiye, 2011, ss. 22-24
[3] M. Pişkin. (2020, 3 Mart). Yüz tanıma | Mesut Pişkin. [Online]. Erişim:http://mesutpiskin.com/blog/yuz-tanima.html.
[4] E. Cengil ve A. Çınar, “A new approach for ımage classification: Convolutional neural network,”European Journal of Technic EJT, c. 6, s. 2, ss. 96–103, 2016.
[5] A. Zhou, J. Chen, J. Ding ve Z. Pan, “Face recognition based on two-stage cnn combined with transfer learning,” 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), Xiamen, China, 2020, ss. 401-406.
[6] F. Ayata, H. Çavuş, M. İnan, E. Seyyarer, E. Biçek ve E. Kına, “Dostroajan: Facial recognition based system input control agent,”AJIT-e: Online Academic Journal of Information Technology, c. 11, s. 40, ss. 82–96, 2020.
[7] R. Godbole ve S. Burad, “Face expression detection using CNN,” International Journal of İnnovative Research in Technolgy, c. 5, s. 12, ss. 16–18, 2019.
[8] O. Çeliktutan, Ç. H. Akakın ve B. Sankur, “İnsan yüzlerinde 2b nirengi noktalarının otomatik saptanması,” IEEE 16th Signal Processing, Communication and Applications Conference, 2013, ss. 1-27.
[9] N. Wang, X. Gao, D. Tao ve W. Liu, “Facial feature point detection: A comprehensive survey,” Neurocomputing,c. 275, ss. 50-65, 2014.
[10] X. Cao, Y. Wei ve F. Wen, “Face alignment by explicit shape regression,” 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012, ss. 2887-2894.
[11] Z. Feng, J. Kittler, L. Member, W. Christmas ve X. Wu, “A unified tensor-based active appearance face model,” ACM Transactions on Multimedia Computing Communications and Applications, 2017, ss. 1–12.
[12] Z. Zhang, P. Luo, C. LoyveX. Tang, “Facial landmark detection by deep multi-task learning,” European Conference on Computer Vision, Springer, 2014, ss. 94-108.
[13] U. Ayvaz ve H. Gürüler, “Bilgisayar kullanıcılarına yönelik duygusal ifade tespiti,” Bilişim Teknolojileri Dergisi, c. 10, ss. 231–231, 2017.
[14] T. Whitmarsh, R. Veltkamp, M. Spagnuolo, S. Marini ve F. Haar, “Landmarkdetection on 3d facescansbyfacial model registration,” 1st İnternational Symposium on Shapes and Semantics, Citeseer, 2008, ss. 71–5.
[15] D. Liu, J. Li, N. Wang, C. Peng ve X. Gao, “Composite components-based faces ketch recognition,” Neurocomputing, c. 302, ss. 46-54, 2018.
[16] A. K. Jain, B. Klare ve U. Park, “Face matching and retrieval in forensics applications”, IEEE Multi Media,c. 19, ss. 1-20, 2012.
[17] S. M. Iranmanesh, H. Kazemi, S. Soleymani, A. Dabouei ve N. M. Nasrabadi, “Deep sketch-photo face recognition assisted by facial attributes,” 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS), RedondoBeach, CA, USA, 2018, ss.1-10.
[18] Q. Wan ve K. Panetta, “A Facial recognition system formatching computerized composite sketches to facial photos using human visual system algorithms,” 2016 IEEE Symposium on Technologies for Homeland Security (HST), 2016, ss. 1-6.
[19] B. Akpınar, “Görüntü sınıflandırma için derin öğrenme ile bayesçi derin öğrenme yöntemlerinin karşılaştırılması,” Yüksek lisans tezi, İstatistik, Fen Bilimleri Enstitüsü, Afyonkarahisar Üniversitesi, Afyon,Türkiye, 2019.
[20] S. Akay, “Facial action unit detection in videos using deep neural networks,” Yüksek lisans tezi, Bilgisayar Mühendisliği, Fen Bilimleri Enstitüsü, Bahçeşehir Üniversitesi, İstanbul, Türkiye, 2018.
[21] A. Hanilçi, “Evrişimsel sinir ağları kullanılarak ekg ve yüz tabanlı biyometrik tanıma,” Yüksek lisans tezi, Elektrik-Elektronik Mühendisliği, Fen Bilimleri Enstitüsü, Bursa Teknik Üniversitesi, Bursa, Türkiye, 2019.
[22] M. Coşkun, A. Uçar, Ö. Yıldırım ve Y. Demir, “Face recognition based on convolutional neural network,” 2017 International Conference on Modern Electrical and Energy Systems (MEES), IEEE, Kremenchuk, Ukraine, 2017, ss. 376-379.
[23] J. Sung ve D. Kim, “A background robust active appearance model using active contour technique,” Pattern Recognition. c. 40, ss. 108-120, 2007.
[24] R. Shbib ve S. Zhou,“Facial expression analysis using active shape model,” International Journal of Signal Processing, Image Processing and Pattern Recognition,c. 8, ss. 9-22, 2015.
[25] P. Martins, “Active appearance models for facial expression recognition and monocular head pose estimation,” Doktora tezi, Elektrik ve Bilgisayar Mühendisliği, Coimbra Üniversitesi, Coimbra, 2008.
[26] N. Vandeput. (2020, 28 Ekim). ForecastKPIs: RMSE, MAE, MAPE Bias. [Online]. Erişim: https://towardsdatascience.com/forecast-kpi-rmse-mae-mape-bias-cdc5703d242d.
[27] C. D. Lewis, Industrial and Business Forecasting Methods. Londra: Butterworths Publishing, Boston, London, 1982.
[28] C. Turhan, G. Gökçen ve T. Kazanasmaz, “Yapay sinir ağlari ile İzmir’deki çok katli binalarin toplam enerji tüketİmlerinin tahmin edilmesi,” 11. Ulusal Tesisat Mühendisliği Kongresi, İzmir, 2013, ss. 411-422.
[29] H. Talandova, L. Kralik ve M. Adamek, “Determination of the uncertaintiesand the physiological similarities of family members by using the biometric device the broadway 3D,” International Journal of Applied Engineering Research, c.11, ss. 6373-6375, 2016.
[30] M. Dehshibi, J. Shanbezadeh ve M. Alavi, “Facial family similarity recognition using local gaborbinary pattern histogram sequence,” 2012 12th International Conference on Hybrid Intelligent Systems (HIS), IEEE, 2012, ss. 219-224.
[31] C. Zhang ve Z. Zhang, “A survey of recent advances in face detection,” Learning-Technical Report MSR-TR-2010-66, https://doi.org/10.1.1.167.5270, 2011.
[32] H. Han, B. Klare, K. Bonnen ve A. Jain, “Matching composite sketches to face photos: a component based approach,” IEEE Transactions on Information Forensics and Security, c. 8, ss. 191-204, 2013.
[33] S. Klum, H. Han, A. Jain ve B. Klare, “Sketch based face recognition: forensic vs. composite sketches,” International Conference on Biometrics (ICB), IEEE, 2013, ss. 1-8.
[34] E. Alimovski ve G. Erdemir , "Veri Artırma Tekniklerinin Derin Öğrenmeye Dayalı Yüz Tanıma Sisteminde Etkisi", İstanbul Sabahattin Zaim Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 3, sayı. 1, ss. 76-80, Nis. 2021.
[35] İ. Akgül, V. Kaya ve A. Baran, "Examination of facial mask detection using deep learning methods against coronavirus," 4. Uluslararası İpek Yolu Akademik Çalışmalar Sempozyumu, Nevşehir, Turkey, ss.149-154, 2021.