activity
20202023
most citedImplementing simple spectral denoising for environmental audio recordings

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2023

Evaluation of Barlow Twins and VICReg self-supervised learning for sound patterns of bird and anuran species

Fábio Felix Dias, Moacir Antonelli Ponti, Mílton Cezar Ribeiro +1

Taking advantage of the structure of large datasets to pre-train Deep Learning models is a promising strategy to decrease the need for supervised data. Self-supervised learning met…

econ.GN2022

Weak Supervision in Analysis of News: Application to Economic Policy Uncertainty

Paul Trust, Ahmed Zahran, Rosane Minghim

The need for timely data analysis for economic decisions has prompted most economists and policy makers to search for non-traditional supplementary sources of data. In that context…

cs.HC2022

Understanding High Dimensional Spaces through Visual Means Employing Multidimensional Projections

Haseeb Younis, Paul Trust, Rosane Minghim

Data visualisation helps understanding data represented by multiple variables, also called features, stored in a large matrix where individuals are stored in lines and variable val…

cs.LG2022

A Visual Analytics Approach to Building Logistic Regression Models and its Application to Health Records

Erasmo Artur, Rosane Minghim

Multidimensional data analysis has become increasingly important in many fields, mainly due to current vast data availability and the increasing demand to extract knowledge from it…

cs.SD2022★ 2 cited

Implementing simple spectral denoising for environmental audio recordings

Fábio Felix Dias, Moacir Antonelli Ponti, Rosane Minghim

This technical report details changes applied to a noise filter to facilitate its application and improve its results. The filter is applied to denoise natural sounds recorded in t…

cs.HC2020

A Visual Mining Approach to Improved Multiple-Instance Learning

Sonia Castelo, Moacir Ponti, Rosane Minghim

Multiple-instance learning (MIL) is a paradigm of machine learning that aims to classify a set (bag) of objects (instances), assigning labels only to the bags. This problem is ofte…