The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK
Abstract
This paper describes an algorithm for verification of signatures written on a pen-input tablet. The algorithm is based on a novel, artificial neural network, called a "Siamese" neural network. This network consists of two identical sub-networks joined at their outputs. During training the two sub-networks extract features from two signatures, while the joining neuron measures the distance between the two feature vectors. Verification consists of comparing an extracted feature vector with a stored feature vector for the signer. Signatures closer to this stored representation than a chosen threshold are excepted, all other signatures are rejected as forgeries.
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“Most of the image registration methods using deep learning are based on a Siamese network (Bromley et al., 1994;Merkle et al., 2017;He et al., 2018;Hughes et al., 2018a;Wang et al., 2018b).”
From Deep learning in remote sensing applications: A meta-analysis and review (2019) · cites this paper as Bromley et al., 1994
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Metadata
- Authors
- BROMLEY, J., BENTZ, J. W., BOTTOU, L., GUYON, I., LECUN, Y., MOORE, C., SÄCKINGER, E., & SHAH, R.
- Affiliations
- AT&T (United States) (US)
- Venue
- Series in Machine Perception and Artificial Intelligence
- Publisher
- WORLD SCIENTIFIC
- Published
- 1994-01
- Pages
- 25-44
- ISSN
- 1793-0839 (ISSN-L)
- OpenAlex
- W2127589108
- Cited by
- 2,350
- References
- 8
- Citations by year
- 2026: 47 · 2025: 148 · 2024: 177 · 2023: 218 · 2022: 212 · 2021: 350 · 2020: 409 · 2019: 339 · 2018: 194 · 2017: 100 · 2016: 68 · 2015: 36 · 2014: 8 · 2013: 4 · 2012: 6
- FWCI
- 0.85
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Series in machine perception and artificial intelligence (publishedVersion)
- Open Research Online (The Open University) (acceptedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Handwritten Text Recognition Techniques
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Keywords
- signature verification, Siamese network, time-delay neural networks, feature extraction, forgery detection, biometric authentication
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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