4.7 Article

A multi-task approach for contrastive learning of handwritten signature feature representations

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

From text to signatures: Knowledge transfer for efficient deep feature learning in offline signature verification

Dimitrios Tsourounis et al.

Summary: The study focuses on improving the efficiency of CNN in offline signature verification task by employing prior knowledge from a similar writer identification task. It demonstrates that pre-training in writer identification and metric learning can significantly enhance the performance of signature verification, even with fewer training samples. Utilizing writer-dependent classifiers and tailored features, the proposed scheme achieves high accuracy comparable to popular approaches despite smaller training sets and absence of skilled forgery signatures during training.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Computer Science, Artificial Intelligence

Learning the micro deformations by max-pooling for offline signature verification

Yuchen Zheng et al.

Summary: This paper demonstrates the potential of Convolutional Neural Networks (CNNs) to extract micro deformations for signature verification systems by watching the location coordinates of maximum values in pooling windows of max-pooling. The proposed method outperforms state-of-the-art systems on multiple publicly available datasets of different languages.

PATTERN RECOGNITION (2021)

Article Computer Science, Artificial Intelligence

Offline signature verification using a region based deep metric learning network

Li Liu et al.

Summary: This paper proposes a region-based Deep Convolutional Siamese Network for offline handwritten signature verification, applicable to both writer-dependent and writer-independent scenarios. By comparing and fusing features from local regions, the method achieves state-of-the-art performance on public datasets.

PATTERN RECOGNITION (2021)

Article Computer Science, Hardware & Architecture

Deep Learning for AI

Yoshua Bengio et al.

Summary: Research on artificial neural networks is motivated by the observation that human intelligence emerges from parallel networks of simple non-linear neurons, leading to the question of how these networks can learn complicated internal representations.

COMMUNICATIONS OF THE ACM (2021)

Review Engineering, Multidisciplinary

A Survey on Contrastive Self-Supervised Learning

Ashish Jaiswal et al.

Summary: Self-supervised learning, particularly through contrastive learning, has gained popularity for its cost-effective approach in using self-defined pseudolabels for various downstream tasks. This paper extensively reviews self-supervised methods following the contrastive approach, explaining pretext tasks and different architectures used. Performance comparisons across multiple downstream tasks demonstrate variations in method effectiveness.

TECHNOLOGIES (2021)

Article Computer Science, Theory & Methods

Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation

Teruo M. Maruyama et al.

Summary: This study introduces a method to automatically model the most common writer variability traits in order to generate offline signatures and train ASVS. The results demonstrate that using specific techniques to generate duplicates significantly improves the performance of ASVS.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2021)

Article Computer Science, Artificial Intelligence

A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification

Victor L. F. Souza et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

Article Computer Science, Artificial Intelligence

Multi-representational learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs

Saeed Masoudnia et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Signature verification approach using fusion of hybrid texture features

Ankan Kumar Bhunia et al.

NEURAL COMPUTING & APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Writer independent offline signature verification based on asymmetric pixel relations and unrelated training-testing datasets

Elias N. Zois et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Patch-based offline signature verification using one-class hierarchical deep learning

Sima Shariatmadari et al.

INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION (2019)

Article Computer Science, Artificial Intelligence

Fixed-sized representation learning from offline handwritten signatures of different sizes

Luiz G. Hafemann et al.

INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION (2018)

Proceedings Paper Computer Science, Artificial Intelligence

A writer-independent approach for offline signature verification using deep convolutional neural networks features

Victor L. F. Souza et al.

2018 7TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS) (2018)

Article Computer Science, Artificial Intelligence

Generation of Duplicated Off-Line Signature Images for Verification Systems

Moises Diaz et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Computer Science, Artificial Intelligence

A Behavioral Handwriting Model for Static and Dynamic Signature Synthesis

Miguel A. Ferrer et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Computer Science, Artificial Intelligence

Handwritten signature verification using the quad-tree histogram of templates and a Support Vector-based artificial immune classification

Yasmine Serdouk et al.

IMAGE AND VISION COMPUTING (2017)

Article Computer Science, Artificial Intelligence

Learning features for offline handwritten signature verification using deep convolutional neural networks

Luiz G. Hafemann et al.

PATTERN RECOGNITION (2017)

Article Computer Science, Hardware & Architecture

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky et al.

COMMUNICATIONS OF THE ACM (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Densely Connected Convolutional Networks

Gao Huang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Beyond triplet loss: a deep quadruplet network for person re-identification

Weihua Chen et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Computer Science, Artificial Intelligence

New off-line Handwritten Signature Verification method based on Artificial Immune Recognition System

Yasmine Serdouk et al.

EXPERT SYSTEMS WITH APPLICATIONS (2016)

Article Computer Science, Theory & Methods

One-Class Writer-Independent Offline Signature Verification Using Feature Dissimilarity Thresholding

Assia Hamadene et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2016)

Article Computer Science, Artificial Intelligence

Offline signature verification and quality characterization using poset-oriented grid features

Elias N. Zois et al.

PATTERN RECOGNITION (2016)

Article Computer Science, Artificial Intelligence

Deep Multitask Metric Learning for Offline Signature Verification

Amir Soleimani et al.

PATTERN RECOGNITION LETTERS (2016)

Article Computer Science, Artificial Intelligence

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Kaiming He et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015)

Article Computer Science, Artificial Intelligence

Multi-feature extraction and selection in writer-independent off-line signature verification

Dominique Rivard et al.

INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION (2013)

Article Computer Science, Artificial Intelligence

Offline signature verification and identification using distance statistics

MK Kalera et al.

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (2004)

Article Engineering, Electrical & Electronic

MCYT baseline corpus: a bimodal biometric database

J Ortega-Garcia et al.

IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING (2003)