Results 261 to 270 of about 956,220 (295)

Deep Multitask Metric Learning for Offline Signature Verification

Pattern Recognition Letters, 2016
A new deep multitask learning based metric learning method is proposed.An appropriate architecture is proposed for offline signature verification.The knowledge of other signers' samples is transfered for better accuracy.The proposed method outperforms SVM and Discriminative Deep Metric Learning.It outperforms the accuracy of other published reports ...
Amir Soleimani, Babak Nadjar Araabi, Kazim Fouladi   +2 more
openaire   +2 more sources

Offline Handwritten Signature Verification using Zernike Moments

2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2015
In this paper, a novel approach for the verification of offline handwritten signatures is proposed. Despite tremendous growth of digital technologies in the last 4 decades, the most used authentication method today remains to be handwritten signature. It is the most natural method of authenticating a person's identity as compared to other biometric and
Harman Preet Kaur, Anmol Sharma
openaire   +2 more sources

Offline Signature Verification with Attention

SSRN Electronic Journal, 2023
Zhuohui Chen, Zhicong Lin, Guanru Zou, Ling Chen   +3 more
openaire   +1 more source

Offline Signature Identification and Verification Using Capsule Network

2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA), 2019
In offline signature identification and verification systems, hand -crafted feature extraction methods, such as local binary patterns, have recently been set aside for automatic feature extraction methods such as convolutional neural networks (CNN). Although these CNN-based algorithms often obtain satisfying results, they require either many samples to
Dilara Gumusbas, Tulay Yildirim
openaire   +2 more sources

Offline Signature Verification Using Artificial Neural Network

2015
In this paper, we have used a neural networks (NN)-based approach to train the offline signature classifier and use it to classify and recognize samples based on some predecided feature sets. We have taken five parameters as a part of the feature set area, mean, standard deviation, centroid value, and the number of even-positioned black pixels.
Chandra Subhash, Sushila Maheshkar, Srivastava Kislay   +2 more
openaire   +1 more source

Learning Generalisable Representations for Offline Signature Verification

2022 International Joint Conference on Neural Networks (IJCNN), 2022
Xianmu Cairang, Duoji Zhaxi, Xiaolong Yang, Yan Hou, Qijun Zhao, Dingguo Gao, Pubu Danzeng, Dorji Gesang   +7 more
openaire   +2 more sources

Recurrent Binary Patterns and CNNs for Offline Signature Verification

2019
Signature representations that are extracted by convolutional neural networks (CNN) can achieve low error rates. However, a trade-off exists between such models’ complexities and hand-crafted features’ slightly higher error rates. A novel writer-dependent (WD) recurrent binary pattern (RBP) network, and a novel signer identification CNN is proposed ...
Yılmaz, Mustafa Berkay, Özturk, Kağan
openaire   +1 more source

A new wrapper feature selection method for language-invariant offline signature verification

Expert Systems With Applications, 2021
Ram Sarkar, Trinav Bhattacharyya, Bitanu Chatterjee   +2 more
exaly  

CBCapsNet: A novel writer-independent offline signature verification model using a CNN-based architecture and capsule neural networks

Expert Systems With Applications, 2021
Mohammad Amini
exaly  

Machine learning-based offline signature verification systems: A systematic review

Signal Processing: Image Communication, 2021
Ghulam Murtaza, Rodina Ahmad, Laiha Mat Kiah   +2 more
exaly