1 code implementation • 16 Jun 2022 • Mariana A. Souza, Robert Sabourin, George D. C. Cavalcanti, Rafael M. O. Cruz
Class imbalance is a characteristic known for making learning more challenging for classification models as they may end up biased towards the majority class.
2 code implementations • 20 May 2022 • Reza Davtalab, Rafael M. O. Cruz, Robert Sabourin
Most dynamic ensemble selection (DES) methods utilize the K-Nearest Neighbors (KNN) algorithm to estimate the competence of classifiers in a small region surrounding the query sample.
no code implementations • 3 Nov 2020 • Marcos Monteiro, Alceu S. Britto Jr, Jean P. Barddal, Luiz S. Oliveira, Robert Sabourin
This paper describes a classifier pool generation method guided by the diversity estimated on the data complexity and classifier decisions.
no code implementations • 29 Oct 2020 • Andre G. Hochuli, Alceu S. Britto Jr, David A. Saji, Jose M. Saavedra, Robert Sabourin, Luiz S. Oliveira
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby imposing substantial constraints on the final performance.
no code implementations • 19 Oct 2020 • Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz, Robert Sabourin
We proposed a method based on a global validation strategy with an external archive to control overfitting during the search for the most discriminant representation.
no code implementations • 13 Oct 2020 • Teruo M. Maruyama, Luiz S. Oliveira, Alceu S. Britto Jr, Robert Sabourin
The method is used to generate offline signatures in the image and the feature space and train an ASVS.
no code implementations • 16 Jul 2020 • Simon Bernard, Hongliu Cao, Robert Sabourin, Laurent Heutte
Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions.
no code implementations • 6 Jul 2020 • Hongliu Cao, Simon Bernard, Robert Sabourin, Laurent Heutte
Its main challenge is most often to exploit the complementarities between these representations to help solve a classification/regression task.
no code implementations • 7 Apr 2020 • Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz, Robert Sabourin
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 Verification (HSV).
no code implementations • 3 Apr 2020 • Victor L. F. Souza, Adriano L. I. Oliveira, Rafael M. O. Cruz, Robert Sabourin
Among the advantages of this framework is its scalability to deal with some of these challenges and its ease in managing new writers, and hence of being used in a transfer learning context.
1 code implementation • 1 Apr 2020 • Mariana A. Souza, Robert Sabourin, George D. C. Cavalcanti, Rafael M. O. Cruz
Our proposed framework builds a multi-label meta-classifier responsible for recommending a set of relevant model types based on the local data complexity of the region surrounding each test sample.
no code implementations • 28 Mar 2020 • Andre G. Hochuli, Alceu S. Britto Jr., Jean P. Barddal, Luiz E. S. Oliveira, Robert Sabourin
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 recognized by a YoLo-based model.
1 code implementation • 17 Oct 2019 • Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
This is particularly challenging for skilled forgeries, where a forger practices imitating the user's signature, and often is able to create forgeries visually close to the original signatures.
no code implementations • 26 Sep 2019 • Regis Antonio Saraiva Albuquerque, Albert Franca Josua Costa, Eulanda Miranda dos Santos, Robert Sabourin, Rafael Giusti
We propose an online method for concept driftdetection based on dynamic classifier ensemble selection.
2 code implementations • 10 Jan 2019 • 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 systems.
5 code implementations • 23 Nov 2018 • Jérôme Rony, Luiz G. Hafemann, Luiz S. Oliveira, Ismail Ben Ayed, Robert Sabourin, Eric Granger
Research on adversarial examples in computer vision tasks has shown that small, often imperceptible changes to an image can induce misclassification, which has security implications for a wide range of image processing systems.
no code implementations • 22 Nov 2018 • Rafael M. O. Cruz, Mariana A. Souza, Robert Sabourin, George D. C. Cavalcanti
Hence, this paper presents an empirical analysis of dynamic selection techniques and data preprocessing methods for dealing with multi-class imbalanced problems.
no code implementations • 1 Nov 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
The meta-features are computed using the training data and used to train a meta-classifier that is able to predict whether or not a base classifier from the pool is competent enough to classify an input instance.
no code implementations • 1 Nov 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
In this paper, we propose improvements to the training and generalization phase of the META-DES framework.
no code implementations • 1 Nov 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
The key issue in Dynamic Ensemble Selection (DES) is defining a suitable criterion for calculating the classifiers' competence.
no code implementations • 1 Nov 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
The more important step in DES techniques is estimating the competence of the base classifiers for the classification of each specific test sample.
no code implementations • 1 Oct 2018 • Rafael M. O. Cruz, Dayvid V. R. Oliveira, George D. C. Cavalcanti, Robert Sabourin
Despite being very effective in several classification tasks, Dynamic Ensemble Selection (DES) techniques can select classifiers that classify all samples in the region of competence as being from the same class.
no code implementations • 30 Sep 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti, Tsang Ing Ren
The meta-features are extracted from the training data and used to train a meta-classifier to predict whether or not a base classifier is competent enough to classify an input instance.
no code implementations • 5 Sep 2018 • Mariana A. Souza, George D. C. Cavalcanti, Rafael M. O. Cruz, Robert Sabourin
Thus, we propose in this work an online pool generation method that produces a locally accurate pool for test samples in difficult regions of the feature space.
no code implementations • 26 Jul 2018 • 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 performance of handwritten signature verification (HSV) when compared to the previous state-of-the-art methods.
no code implementations • 20 Jun 2018 • Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin
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.
no code implementations • 24 Apr 2018 • Andre G. Hochuli, Luiz E. S. Oliveira, Alceu S. Britto Jr, Robert Sabourin
This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length.
no code implementations • 21 Apr 2018 • Rafael M. O. Cruz, Hiba H. Zakane, Robert Sabourin, George D. C. Cavalcanti
Experiments are performed on 18 state-of-the-art DS techniques over 30 classification datasets and results show that DS methods present a significant boost in classification accuracy even though they use the same neighborhood as the K-NN.
no code implementations • 20 Apr 2018 • Felipe N. Walmsley, George D. C. Cavalcanti, Dayvid V. R. Oliveira, Rafael M. O. Cruz, Robert Sabourin
Techniques such as Bagging and Boosting have been successfully applied to a variety of problems.
no code implementations • 18 Apr 2018 • Dayvid V. R. Oliveira, George D. C. Cavalcanti, Thyago N. Porpino, Rafael M. O. Cruz, Robert Sabourin
The K-Nearest Oracles Eliminate (KNORA-E) DES selects all classifiers that correctly classify all samples in the region of competence of the test sample, if such classifier exists, otherwise, it removes from the region of competence the sample that is furthest from the test sample, and the process repeats.
1 code implementation • 2 Apr 2018 • 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 Networks to learn representations from signature pixels.
no code implementations • 29 Mar 2018 • Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin
In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer learning feature extractors based on deep learning.
no code implementations • 12 Mar 2018 • Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin
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 prognostic information.
no code implementations • 11 Mar 2018 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
Hence, this paper presents an empirical analysis of dynamic selection techniques and data preprocessing methods for dealing with multi-class imbalanced problems.
no code implementations • 27 Feb 2018 • Saman Bashbaghi, Eric Granger, Robert Sabourin, Mostafa Parchami
In video-based FR systems, facial models of target individuals are designed a priori during enrollment using a limited number of reference still images or video data.
2 code implementations • 14 Feb 2018 • Rafael M. O. Cruz, Luiz G. Hafemann, Robert Sabourin, George D. C. Cavalcanti
DESlib is an open-source python library providing the implementation of several dynamic selection techniques.
4 code implementations • 16 May 2017 • 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 deliberately attempt to imitate it.
no code implementations • 15 Jul 2016 • 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.
no code implementations • 20 May 2016 • Julien-Charles Lévesque, Christian Gagné, Robert Sabourin
Our method consists in building a fixed-size ensemble, optimizing the configuration of one classifier of the ensemble at each iteration of the hyperparameter optimization algorithm, taking into consideration the interaction with the other models when evaluating potential performances.
no code implementations • 4 Apr 2016 • 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, signal processing, among others.
no code implementations • 2 Sep 2015 • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
In order to perform a more robust ensemble selection, we proposed the META-DES framework using meta-learning, where multiple criteria are encoded as meta-features and are passed down to a meta-classifier that is trained to estimate the competence level of a given classifier.
no code implementations • 28 Jul 2015 • 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.
no code implementations • 1 Jul 2015 • Guillaume Corriveau, Raynald Guilbault, Antoine Tahan, Robert Sabourin
Numerous genotypic diversity measures (GDMs) are available in the literature to assess the convergence status of an evolutionary algorithm (EA) or describe its search behavior.
no code implementations • 18 Aug 2014 • 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 private cryptographic keys.
no code implementations • 13 Aug 2014 • Albert H. R. Ko, Robert Sabourin, Alceu S. Britto Jr, Luiz E. S. Oliveira
Our scheme is the first ensemble selection method to be presented in the literature based on the concept of data diversity.