HYBRID AUTO ENCODER–CNN FRAMEWORK FOR OFFLINE SIGNATURE FORGERY DETECTION
DOI:
https://doi.org/10.48047/wh3wjs88Keywords:
Offline Signature Verification, Signature Forgery Detection, Auto encoder, Convolutional Neural Network (CNN), Support Vector Machine (SVM), Deep Learning.Abstract
Handwritten Signature Verification remains crucial in secure authentication systems of banking, legal papers, financial transactions, and ID management, particularly in an offline environment. Traditional verification methods, however, can be very weak in achieving high rates of accuracy for skilled forgeries, as they rely on handcrafted features and have a high sensitivity to variations in handwriting. The authors propose a hybrid deep learning
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