BIR SINFLI TAYANCH VEKTOR MASHINALARI (ONE-CLASS SVM) ASOSIDA SHAXS IMZOSINI ANIQLASHNING SAMARADORLIGI
Abstract
Mazkur maqolada shaxs imzosini avtomatik tarzda aniqlash va verifikatsiyalashda bir sinfli tayanch vektor mashinalari (One-Class SVM) modelidan foydalanish imkoniyatlari ko‘rib chiqiladi. Modelning ishlash prinsipi, uning boshqa usullardan afzalliklari va real eksperimental natijalar asosida samaradorlik darajasi yoritiladi.
Downloads
References
Schölkopf, B., Platt, J.C., Shawe-Taylor, J., Smola, A.J., & Williamson, R.C. (2001). Estimating the support of a high-dimensional distribution. Neural Computation, 13(7), 1443–1471.
Tax, D.M.J. & Duin, R.P.W. (2004). Support vector data description. Machine Learning, 54(1), 45–66.
Hafemann, L.G., Oliveira, L.S., & Sabourin, R. (2017). Offline handwritten signature verification — literature review. arXiv preprint arXiv:1705.05787.
Riesz, C., Ferrer, M.A., & Impedovo, D. (2019). Signature verification: State-of-the-art and current challenges. Computer Vision and Image Understanding, 181, 1–20.
Chollet, F. (2018). Deep Learning with Python. Manning Publications.
Vapnik, V. (1998). Statistical Learning Theory. Wiley-Interscience.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273–297.