no code implementations • 18 Apr 2024 • Luciana Trinkaus Menon, Luiz Carlos Ribeiro Neduziak, Jean Paul Barddal, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr
The study of human emotions, traditionally a cornerstone in fields like psychology and neuroscience, has been profoundly impacted by the advent of artificial intelligence (AI).
no code implementations • 18 Apr 2024 • Israel A. Laurensi, Alceu de Souza Britto Jr., Jean Paul Barddal, Alessandro Lameiras Koerich
Facial expression recognition is a pivotal component in machine learning, facilitating various applications.
no code implementations • 18 Mar 2024 • Cristiano Mesquita Garcia, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr, Jean Paul Barddal
The proliferation of textual data on the Internet presents a unique opportunity for institutions and companies to monitor public opinion about their services and products.
no code implementations • 18 Mar 2024 • Cristiano Mesquita Garcia, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr, Jean Paul Barddal
To learn from textual data over time, the machine learning system must account for concept drift.
1 code implementation • 15 Mar 2024 • Paul Waligora, Haseeb Aslam, Osama Zeeshan, Soufiane Belharbi, Alessandro Lameiras Koerich, Marco Pedersoli, Simon Bacon, Eric Granger
Multimodal emotion recognition (MMER) systems typically outperform unimodal systems by leveraging the inter- and intra-modal relationships between, e. g., visual, textual, physiological, and auditory modalities.
1 code implementation • 1 Feb 2024 • Soufiane Belharbi, Marco Pedersoli, Alessandro Lameiras Koerich, Simon Bacon, Eric Granger
During training, this \au codebook is used, along with the input image expression label, and facial landmarks, to construct a \au heatmap that indicates the most discriminative image regions of interest w. r. t the facial expression.
Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 9 Dec 2023 • Muhammad Osama Zeeshan, Muhammad Haseeb Aslam, Soufiane Belharbi, Alessandro Lameiras Koerich, Marco Pedersoli, Simon Bacon, Eric Granger
It efficiently leverages information from multiple source subjects (labeled source domain data) to adapt a deep FER model to a single target individual (unlabeled target domain data).
Facial Expression Recognition Facial Expression Recognition (FER) +2
no code implementations • 5 Dec 2023 • Cristiano Mesquita Garcia, Ramon Simoes Abilio, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr., Jean Paul Barddal
Due to the advent and increase in the popularity of the Internet, people have been producing and disseminating textual data in several ways, such as reviews, social media posts, and news articles.
no code implementations • 17 Jun 2022 • Jonathan de Matos, Luiz Eduardo Soares de Oliveira, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich
The core of such an approach is a loss function that computes the distances between instances of interest and support vectors.
no code implementations • 14 Apr 2022 • 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 victim residual convolutional neural network, namely ResNet-18.
no code implementations • 27 Feb 2022 • Steve Tsham Mpinda Ataky, Alessandro Lameiras Koerich
Texture descriptors have been quite popular in medical image analysis, particularly in histopathologic images (HI), due to the variability of both the texture found in such images and the tissue appearance due to irregularity in the staining process.
no code implementations • 15 Mar 2021 • 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.
no code implementations • 15 Mar 2021 • 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.
1 code implementation • 13 Feb 2021 • 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 on the surface.
no code implementations • 7 Feb 2021 • Jonathan de Matos, Steve Tsham Mpinda Ataky, Alceu de Souza Britto Jr., Luiz Eduardo Soares de Oliveira, Alessandro Lameiras Koerich
Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis.
no code implementations • 18 Nov 2020 • Thomas Teixeira, Eric Granger, Alessandro Lameiras Koerich
In this paper, we investigate the suitability of state-of-the-art deep learning architectures based on convolutional neural networks (CNNs) for continuous emotion recognition using long video sequences captured in-the-wild.
no code implementations • 22 Oct 2020 • 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.
no code implementations • 12 Oct 2020 • Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges, Patrick Cardinal, Alessandro Lameiras Koerich
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.
no code implementations • 12 Aug 2020 • Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges, Patrick Cardinal, Alessandro Lameiras Koerich
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 representations of audio and speech signals.
no code implementations • 27 Jul 2020 • 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 of a victim residual convolutional neural network.
no code implementations • 26 Oct 2019 • Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
Adversarial attacks have always been a serious threat for any data-driven model.
1 code implementation • 22 Oct 2019 • Karl Michel Koerich, Mohammad Esmaeilpour, Sajjad Abdoli, Alceu de Souza Britto Jr., Alessandro Lameiras Koerich
Furthermore, the audio waveforms reconstructed from the perturbed spectrograms are also able to fool a 1D CNN trained on the original audio.
no code implementations • 22 Jul 2019 • Kelly Lais Wiggers, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich, Laurent Heutte, Luiz Eduardo Soares de Oliveira
This paper describes two approaches for content-based image retrieval and pattern spotting in document images using deep learning.
1 code implementation • 22 Jul 2019 • Alexandre Reeberg de Mello, Marcelo Ricardo Stemmer, Alessandro Lameiras Koerich
In this paper we present an incremental variant of the Twin Support Vector Machine (TWSVM) called Fuzzy Bounded Twin Support Vector Machine (FBTWSVM) to deal with large datasets and learning from data streams.
no code implementations • 6 Jul 2019 • Mohammed Senoussaoui, Patrick Cardinal, Alessandro Lameiras Koerich
The conventional BoW model is based on a dictionary (codebook) built from elementary representations which are selected randomly or by using a clustering algorithm on a training dataset.
no code implementations • 26 Apr 2019 • Alexandre Reeberg Mello, Jonathan de Matos, Marcelo R. Stemmer, Alceu de Souza Britto Jr., Alessandro Lameiras Koerich
In this paper, we propose the use of a black-box optimization method called deterministic Mesh Adaptive Direct Search (MADS) algorithm with orthogonal directions (Ortho-MADS) for the selection of hyperparameters of Support Vector Machines with a Gaussian kernel.
no code implementations • 26 Apr 2019 • Mohammed Senoussaoui, Patrick Cardinal, Najim Dehak, Alessandro Lameiras Koerich
Automatic measuring of speaker sincerity degree is a novel research problem in computational paralinguistics.
no code implementations • 24 Apr 2019 • Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we first review some strong adversarial attacks that may affect both audio signals and their 2D representations and evaluate the resiliency of the most common machine learning model, namely deep learning models and support vector machines (SVM) trained on 2D audio representations such as short time Fourier transform (STFT), discrete wavelet transform (DWT) and cross recurrent plot (CRP) against several state-of-the-art adversarial attacks.
3 code implementations • 18 Apr 2019 • Sajjad Abdoli, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper, we present an end-to-end approach for environmental sound classification based on a 1D Convolution Neural Network (CNN) that learns a representation directly from the audio signal.
Ranked #6 on Environmental Sound Classification on UrbanSound8K (Accuracy metric, using extra training data)
Environmental Sound Classification General Classification +1
no code implementations • 8 Apr 2019 • Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we propose a novel environmental sound classification approach incorporating unsupervised feature learning from codebook via spherical $K$-Means++ algorithm and a new architecture for high-level data augmentation.