27 citations · 52 across the 5 of their papers we have counts for
6 papers
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels
Martha Dais Ferreira, Gabriel Spadon, Amilcar Soares +1
Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data plays a signi…
Unfolding AIS transmission behavior for vessel movement modeling on noisy data leveraging machine learning
Gabriel Spadon, Martha D. Ferreira, Amilcar Soares +1
The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered. Such data comes from the oceans and their surface…
Active learning for medical code assignment
Martha Dais Ferreira, Michal Malyska, Nicola Sahar +3
Machine Learning (ML) is widely used to automatically extract meaningful information from Electronic Health Records (EHR) to support operational, clinical, and financial decision-m…
Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series
Leonardo Christino, Martha D. Ferreira, Fernando V. Paulovich
Knowing how to construct text-based Search Queries (SQs) for use in Search Engines (SEs) such as Google or Wikipedia has become a fundamental skill. Though much data are available…
Providing theoretical learning guarantees to Deep Learning Networks
Rodrigo Fernandes de Mello, Martha Dais Ferreira, Moacir Antonelli Ponti
Deep Learning (DL) is one of the most common subjects when Machine Learning and Data Science approaches are considered. There are clearly two movements related to DL: the first agg…
Acoustic Modeling Using a Shallow CNN-HTSVM Architecture
Christopher Dane Shulby, Martha Dais Ferreira, Rodrigo F. de Mello +1
High-accuracy speech recognition is especially challenging when large datasets are not available. It is possible to bridge this gap with careful and knowledge-driven parsing combin…