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natural-language-processing

Handwriting Verification

3260 papers • 126 benchmarks • 313 datasets

The goal of handwriting verification is to find a measure of confidence whether the given handwritten samples are written by the same or different writer.

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in handwriting-verification-1

Trend

Dataset

Best Model

Actions

CEDAR Signature

AND Dataset

Libraries

Use these libraries to find handwriting-verification-1 models and implementations

Datasets

Subtasks

Bangla Spelling Error Correction

Most implemented papers

SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification

S. Dey, Anjan Dutta, J. Lladós, J. I. Toledo, Suman K. Ghosh, U. Pal•Thu Jul 06 2017

This paper models an offline writer independent signature verification task with a convolutional Siamese network, named SigNet, and exceeds the state-of-the-art results on most of the benchmark signature datasets, which paves the way for further research in this direction.

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Introduction Benchmarks Datasets Subtasks Libraries Papers

Paper Graph

Hybrid Feature Learning for Handwriting Verification

S. Srihari, Mihir Chauhan, Mohammad Abuzar Shaikh, Jun Chu•Tue Jul 31 2018

The results indicate that HDL architecture with AE-GSC achieves 99.7% accuracy on seen writer dataset and 92.16%" accuracy on shuffled writer dataset which out performs CEDAR-FOX, as for unseen writer dataset, AE-SIFT performs comparable to this sophisticated handwriting comparison tool.

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Paper Graph

Explanation based Handwriting Verification

S. Srihari, Mihir Chauhan, Mohammad Abuzar Shaikh•Tue Aug 13 2019

This work proposes a method to generate explanations for the confidence provided by convolu-tional neural network (CNN) which maps the input image to 15 annotations ( features)provided by experts which can serve as the basis and benchmark for future research in explanation based handwriting verification.

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Paper Graph

MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification

Yuliang Liu, Lianwen Jin, Peirong Zhang, Jiajia Jiang•Sun Oct 16 2022

Surprisingly, verification performances of state-of-the-art methods on MSDS-TDS are generally better than those on MS DS-ChS, which indicates that the handwritten Token Digit String could be a more effective biometric than handwritten Chinese signature.

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Paper Graph

Adding a benchmark result helps the community track progress.

Handwriting Verification | State-of-the-Art