43 citations · 161 across the 35 of their papers we have counts for
45 papers
Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing
Caio da S. Dias, Alceu de S. Britto, Jean P. Barddal +2
This paper presents a deep learning approach for image retrieval and pattern spotting in digital collections of historical documents. First, a region proposal algorithm detects obj…
Large-Margin Representation Learning for Texture Classification
Jonathan de Matos, Luiz Eduardo Soares de Oliveira, Alceu de Souza Britto Junior +1
This paper presents a novel approach combining convolutional layers (CLs) and large-margin metric learning for training supervised models on small datasets for texture classificati…
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition
Bruna Delazeri, Leonardo L. Veras, Alceu de S. Britto +2
This work describes different strategies to generate unsupervised representations obtained through the concept of self-taught learning for facial emotion recognition (FER). The ide…
Named Entity Recognition for Audio De-Identification
Guillaume Baril, Patrick Cardinal, Alessandro Lameiras Koerich
Data anonymization is often a task carried out by humans. Automating it would reduce the cost and time required to complete this task. This paper presents a pipeline to automate th…
Multiscale Analysis for Improving Texture Classification
Steve T. M. Ataky, Diego Saqui, Jonathan de Matos +2
Information from an image occurs over multiple and distinct spatial scales. Image pyramid multiresolution representations are a useful data structure for image analysis and manipul…
From Environmental Sound Representation to Robustness of 2D CNN Models Against Adversarial Attacks
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
This paper investigates the impact of different standard environmental sound representations (spectrograms) on the recognition performance and adversarial attack robustness of a vi…
A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition
R. Gnana Praveen, Wheidima Carneiro de Melo, Nasib Ullah +8
Multimodal emotion recognition has recently gained much attention since it can leverage diverse and complementary relationships over multiple modalities (e.g., audio, visual, biosi…
Texture Characterization of Histopathologic Images Using Ecological Diversity Measures and Discrete Wavelet Transform
Steve Tsham Mpinda Ataky, Alessandro Lameiras Koerich
Breast cancer is a health problem that affects mainly the female population. An early detection increases the chances of effective treatment, improving the prognosis of the disease…
1D CNN Architectures for Music Genre Classification
Safaa Allamy, Alessandro Lameiras Koerich
This paper proposes a 1D residual convolutional neural network (CNN) architecture for music genre classification and compares it with other recent 1D CNN architectures. The 1D CNNs…
Discriminative Singular Spectrum Classifier with Applications on Bioacoustic Signal Recognition
Bernardo B. Gatto, Juan G. Colonna, Eulanda M. dos Santos +2
Automatic analysis of bioacoustic signals is a fundamental tool to evaluate the vitality of our planet. Frogs and bees, for instance, may act like biological sensors providing info…
Towards Robust Speech-to-Text Adversarial Attack
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
This paper introduces a novel adversarial algorithm for attacking the state-of-the-art speech-to-text systems, namely DeepSpeech, Kaldi, and Lingvo. Our approach is based on develo…
Multi-Discriminator Sobolev Defense-GAN Against Adversarial Attacks for End-to-End Speech Systems
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
This paper introduces a defense approach against end-to-end adversarial attacks developed for cutting-edge speech-to-text systems. The proposed defense algorithm has four major ste…
Cyclic Defense GAN Against Speech Adversarial Attacks
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
This paper proposes a new defense approach for counteracting state-of-the-art white and black-box adversarial attack algorithms. Our approach fits into the implicit reactive defens…
Machine Learning Methods for Histopathological Image Analysis: A Review
Jonathan de Matos, Steve Tsham Mpinda Ataky, Alceu de Souza Britto +2
Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming,…
A Novel Bio-Inspired Texture Descriptor based on Biodiversity and Taxonomic Measures
Steve Tsham Mpinda Ataky, Alessandro Lameiras Koerich
Texture can be defined as the change of image intensity that forms repetitive patterns, resulting from physical properties of the object's roughness or differences in a reflection…
Continuous Emotion Recognition with Spatiotemporal Convolutional Neural Networks
Thomas Teixeira, Eric Granger, Alessandro Lameiras Koerich
Facial expressions are one of the most powerful ways for depicting specific patterns in human behavior and describing human emotional state. Despite the impressive advances of affe…
Conditioning Trick for Training Stable GANs
Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges +2
In this paper we propose a conditioning trick, called difference departure from normality, applied on the generator network in response to instability issues during GAN training. W…
Class-Conditional Defense GAN Against End-to-End Speech Attacks
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we propose a novel defense approach against end-to-end adversarial attacks developed to fool advanced speech-to-text systems such as DeepSpeech and Lingvo. Unlike con…
Improving Stability of LS-GANs for Audio and Speech Signals
Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges +2
In this paper we address the instability issue of generative adversarial network (GAN) by proposing a new similarity metric in unitary space of Schur decomposition for 2D represent…
From Sound Representation to Model Robustness
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper, we investigate the impact of different standard environmental sound representations (spectrograms) on the recognition performance and adversarial attack robustness o…
Self-supervised Deep Reconstruction of Mixed Strip-shredded Text Documents
Thiago M. Paixão, Rodrigo F. Berriel, Maria C. S. Boeres +4
The reconstruction of shredded documents consists of coherently arranging fragments of paper (shreds) to recover the original document(s). A great challenge in computational recons…
Two-View Fine-grained Classification of Plant Species
Voncarlos M. Araujo, Alceu S. Britto, Luiz E. S. Oliveira +1
Automatic plant classification is a challenging problem due to the wide biodiversity of the existing plant species in a fine-grained scenario. Powerful deep learning architectures…
Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blending
Steve Tsham Mpinda Ataky, Jonathan de Matos, Alceu de S. Britto +2
Data imbalance is a major problem that affects several machine learning (ML) algorithms. Such a problem is troublesome because most of the ML algorithms attempt to optimize a loss…
Continuous Emotion Recognition via Deep Convolutional Autoencoder and Support Vector Regressor
Sevegni Odilon Clement Allognon, Alessandro L. Koerich, Alceu de S. Britto
Automatic facial expression recognition is an important research area in the emotion recognition and computer vision. Applications can be found in several domains such as medical t…