Acoustic Modeling Using a Shallow CNN-HTSVM Architecture. - Christopher Dane Shulby; Martha Dais Ferreira; Rodrigo Fernandes de Mello; Sandra Maria Aluísio (BRACIS, 2017)

Providing theoretical learning guarantees to Deep Learning Networks. - Rodrigo Fernandes de Mello; Martha Dais Ferreira; Moacir Antonelli Ponti (CoRR, 2017)

Designing architectures of convolutional neural networks to solve practical problems. - Martha Dais Ferreira; Débora Cristina Corrêa; Luis Gustavo Nonato; Rodrigo Fernandes de Mello (Expert Syst. Appl., 2018)

Robust Phoneme Recognition with Little Data. - Christopher Dane Shulby; Martha Dais Ferreira; Rodrigo Fernandes de Mello; Sandra Maria Aluísio (SLATE, 2019)

Theoretical learning guarantees applied to acoustic modeling. - Christopher Dane Shulby; Martha Dais Ferreira; Rodrigo Fernandes de Mello; Sandra M. Aluísio (J. Braz. Comput. Soc., 2019)

Senti-COVID19: An Interactive Visual Analytics System for Detecting Public Sentiment and Insights Regarding COVID-19 From Social Media. - Xuemin Yu; Martha Dais Ferreira; Fernando V. Paulovich (IEEE Access, 2021)

Explainable Patterns: Going from Findings to Insights to Support Data Analytics Democratization. - Leonardo Christino; Martha Dais Ferreira; Asal Jalilvand; Fernando V. Paulovich (CoRR, 2021)

Active learning for medical code assignment. - Martha Dais Ferreira; Michal Malyska; Nicola Sahar; Riccardo Miotto; Fernando V. Paulovich; Evangelos E. Milios (CoRR, 2021)

Capture and Recognition of Bead Weaving Activities using Hand Skeletal Data and an LSTM Deep Neural Network. - Rowland Goddy-Worlu; Martha Dais Ferreira; Matthew Peachey; James Forren; Claire Nicholas; Derek Reilly (AIVR, 2022)

Detection of invalid AIS messages using machine learning techniques. - Jessica N. A. Campbell; Anthony W. Isenor; Martha Dais Ferreira (ICMCIS, 2022)

Unfolding collective AIS transmission behavior for vessel movement modeling on irregular timing data using noise-robust neural networks. - Gabriel Spadon; Martha Dais Ferreira; Amílcar Soares 001; Stan Matwin (CoRR, 2022)

A semi-supervised geometric-driven methodology for supervised fishing activity detection on multi-source AIS tracking messages. - Martha Dais Ferreira; Gabriel Spadon; Amílcar Soares 001; Stan Matwin (CoRR, 2022)

Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series. - Leonardo Christino; Martha Dais Ferreira; Fernando V. Paulovich (Inf., 2022)

Neural network training fingerprint: visual analytics of the training process in classification neural networks. - Martha Dais Ferreira; Gabriel Dias Cantareira; Rodrigo Fernandes de Mello; Fernando V. Paulovich (J. Vis., 2022)

A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels. - Martha Dais Ferreira; Gabriel Spadon; Amílcar Soares 001; Stan Matwin (Sensors, 2022)

Unfolding AIS Transmission Behavior for Vessel Movement Modeling on Noisy Data Leveraging Machine Learning. - Gabriel Spadon; Martha Dais Ferreira; Amílcar Soares 001; Stan Matwin (IEEE Access, 2023)

SGORNN: Combining scalar gates and orthogonal constraints in recurrent networks. - Will Taylor-Melanson; Martha Dais Ferreira; Stan Matwin (Neural Networks, 2023)

Assessing compression algorithms to improve the efficiency of clustering analysis on AIS vessel trajectories. - Martha Dais Ferreira; Jessica N. A. Campbell; Evan Purney; Amílcar Soares 001; Stan Matwin (Int. J. Geogr. Inf. Sci., 2023)

Exploring autoregression patterns for automatic vessel type classification. - Martha Dais Ferreira; Zahra Sadeghi; Stan Matwin (J. Supercomput., 2024)

Generation of Vessel Track Characteristics Using a Conditional Generative Adversarial Network (CGAN). - Jessica N. A. Campbell; Martha Dais Ferreira; Anthony W. Isenor (Appl. Artif. Intell., 2024)

A novel RNN architecture to improve the precision of ship trajectory predictions. - Martha Dais Ferreira; Jessica N. A. Campbell (Appl. Artif. Intell., 2025)