Machine Learning for Signature Verification-Reference-Cited by-同舟云学术

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Machine Learning for Signature Verification

Published:2006 Issue: Volume: Page:761-775
ISSN:0302-9743
Container-title:Computer Vision, Graphics and Image Processing
language:
Short-container-title:

Author:

Srinivasan Harish,Srihari Sargur N.,Beal Matthew J.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11949619_68.pdf

Reference26 articles.

1. Osborn, A.: Questioned Documents. Nelson Hall Pub. (1929)

2. Robertson, E.W.: Fundamentals of Document Examination. Nelson-Hall (1991)

3. Bradford, R.R., Bradford, R.: Introduction to Handwriting Examination and Identification. Nelson-Hall (1992)

4. Hilton, O.: Scientific Examination of Questioned Documents. CRC Press, Boca Raton (1993)

5. Huber, R., Headrick, A.: Handwriting Identification: Facts and Fundamentals. CRC Press, Boca Raton (1999)

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1. A Review on Automated Annotation System for Document Text Images;2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU);2024-03-01

2. A deep learning approach for the comparison of handwritten documents using latent feature vectors;Statistical Analysis and Data Mining: The ASA Data Science Journal;2024-02

3. Enhanced Bank Check Security: Introducing a Novel Dataset and Transformer-Based Approach for Detection and Verification;Lecture Notes in Computer Science;2024

4. Siamese-Transformer Network for Offline Handwritten Signature Verification using Few-shot;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13

5. SigScatNet: A Siamese + Scattering based Deep Learning Approach for Signature Forgery Detection and Similarity Assessment;2023 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom);2023-12-07

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