IMZONI TANIB OLISHDA QO‘LLANILADIGAN ASOSIY ALGORITMLAR: KLASSIK VA ZAMONAVIY METODLARNING SOLISHTIRILGAN TAHLILI
Article Sidebar
Main Article Content
Abstract:
Tadqiqotda imzoni avtomatik tanib olish jarayonida qo‘llaniladigan algoritmlarning turlari va ularning samaradorlik darajasi tahlil qilinadi. Klassik yondashuvlar — Template Matching, Euclidean Distance, Dynamic Time Warping (DTW) — va zamonaviy metodlar — Support Vector Machine (SVM), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) — funksional va texnologik mezonlar asosida solishtirildi. Tadqiqot natijalari klassik metodlar oddiy strukturali tizimlarda samarali bo‘lsa-da, zamonaviy chuqur o‘rganish modellarining aniqlik darajasi, barqarorlik va moslashuvchanlikda ustunligini ko‘rsatdi.
Article Details
How to Cite:
References:
Plamondon, R., & Lorette, G. (1989). Automatic Signature Verification and Writer Identification – The State of the Art. Pattern Recognition, 22(2), 107–131.
Jain, A. K., Ross, A., & Nandakumar, K. (2011). Introduction to Biometrics. Springer.
Maltoni, D., Maio, D., Jain, A. K., & Prabhakar, S. (2009). Handbook of Biometrics. Springer Science & Business Media.
Said, E., Georgiou, T., & Ferrer, M. A. (2019). Offline Signature Verification Using CNNs and Deep Learning Techniques. IET Biometrics, 8(2), 134–142.
Hafemann, L. G., Oliveira, L. S., & Sabourin, R. (2017). Offline handwritten signature verification—literature review. Pattern Recognition, 70, 270–291.