387 citations · 1.6k across the 48 of their papers we have counts for
23 papers · 1 filter
A Prototypical Signature Approach for Writer-Independent Offline Signature Verification
Kecia G. de Moura, Robert Sabourin, Rafael M. O. Cruz
Offline handwritten signature verification aims to distinguish genuine from forged signatures using static images. Since real forgeries are rarely available, negative samples are u…
Offline Handwritten Signature Verification Using a Stream-Based Approach
Kecia G. de Moura, Rafael M. O. Cruz, Robert Sabourin
Handwritten Signature Verification (HSV) systems distinguish between genuine and forged signatures. Traditional HSV development involves a static batch configuration, constraining…
A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition
Andre G. Hochuli, Alceu S. Britto, David A. Saji +3
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby impos…
An Investigation of Feature Selection and Transfer Learning for Writer-Independent Offline Handwritten Signature Verification
Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz +1
SigNet is a state of the art model for feature representation used for handwritten signature verification (HSV). This representation is based on a Deep Convolutional Neural Network…
Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation
Teruo M. Maruyama, Luiz S. Oliveira, Alceu S. Britto +1
Usually, in a real-world scenario, few signature samples are available to train an automatic signature verification system (ASVS). However, such systems do indeed need a lot of sig…
Improving BPSO-based feature selection applied to offline WI handwritten signature verification through overfitting control
Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz +1
This paper investigates the presence of overfitting when using Binary Particle Swarm Optimization (BPSO) to perform the feature selection in a context of Handwritten Signature Veri…
A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification
Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz +1
High number of writers, small number of training samples per writer with high intra-class variability and heavily imbalanced class distributions are among the challenges and diffic…
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings
Andre G. Hochuli, Alceu S. Britto, Jean P. Barddal +2
An end-to-end solution for handwritten numeral string recognition is proposed, in which the numeral string is considered as composed of objects automatically detected and recognize…
Meta-learning for fast classifier adaptation to new users of Signature Verification systems
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
Offline Handwritten Signature verification presents a challenging Pattern Recognition problem, where only knowledge of the positive class is available for training. While classifie…
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
The phenomenon of Adversarial Examples is attracting increasing interest from the Machine Learning community, due to its significant impact to the security of Machine Learning syst…
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses
Jérôme Rony, Luiz G. Hafemann, Luiz S. Oliveira +3
Research on adversarial examples in computer vision tasks has shown that small, often imperceptible changes to an image can induce misclassification, which has security implication…
A writer-independent approach for offline signature verification using deep convolutional neural networks features
Victor L. F. Souza, Adriano L. I. Oliveira, Robert Sabourin
The use of features extracted using a deep convolutional neural network (CNN) combined with a writer-dependent (WD) SVM classifier resulted in significant improvement in performanc…
Dynamic voting in multi-view learning for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Cancer diagnosis and treatment often require a personalized analysis for each patient nowadays, due to the heterogeneity among the different types of tumor and among patients. Radi…
Segmentation-Free Approaches for Handwritten Numeral String Recognition
Andre G Hochuli, Luiz E S Oliveira, Alceu S Britto +1
This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length. A synthetic dataset of touching numeral strings of sizes 2-,…
Fixed-sized representation learning from Offline Handwritten Signatures of different sizes
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
Methods for learning feature representations for Offline Handwritten Signature Verification have been successfully proposed in recent literature, using Deep Convolutional Neural Ne…
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology I…
Dissimilarity-based representation for radiomics applications
Hongliu Cao, Simon Bernard, Laurent Heutte +1
Radiomics is a term which refers to the analysis of the large amount of quantitative tumor features extracted from medical images to find useful predictive, diagnostic or prognosti…
Deep Learning Architectures for Face Recognition in Video Surveillance
Saman Bashbaghi, Eric Granger, Robert Sabourin +1
Face recognition (FR) systems for video surveillance (VS) applications attempt to accurately detect the presence of target individuals over a distributed network of cameras. In vid…
Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
Verifying the identity of a person using handwritten signatures is challenging in the presence of skilled forgeries, where a forger has access to a person's signature and deliberat…
Analyzing features learned for Offline Signature Verification using Deep CNNs
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
Research on Offline Handwritten Signature Verification explored a large variety of handcrafted feature extractors, ranging from graphology, texture descriptors to interest points.…
Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
Automatic Offline Handwritten Signature Verification has been researched over the last few decades from several perspectives, using insights from graphology, computer vision, signa…
Offline Handwritten Signature Verification - Literature Review
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
The area of Handwritten Signature Verification has been broadly researched in the last decades, but remains an open research problem. The objective of signature verification system…
Offline Signature-Based Fuzzy Vault (OSFV: Review and New Results
George S. Eskander, Robert Sabourin, Eric Granger
An offline signature-based fuzzy vault (OSFV) is a bio-cryptographic implementation that uses handwritten signature images as biometrics instead of traditional passwords to secure…