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Details

  • Name

    Elsa Ferreira Gomes
  • Cluster

    Computer Science
  • Role

    Affiliated Researcher
  • Since

    01st November 2016
Publications

2021

Automatic Identification of Bird Species from Audio

Authors
Carvalho, S; Gomes, EF;

Publication
Intelligent Information and Database Systems - 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7-10, 2021, Proceedings

Abstract

2019

Classifying Heart Sounds Using Images of Motifs, MFCC and Temporal Features

Authors
Nogueira, DM; Ferreira, CA; Gomes, EF; Jorge, AM;

Publication
Journal of Medical Systems

Abstract

2018

Studying Programming Students Motivation using Association Rules

Authors
Tavares, PC; Gomes, EF; Henriques, PR;

Publication
Proceedings of the 10th International Conference on Computer Supported Education

Abstract

2017

A Computer Platform to Increase Motivation in Programming Students - PEP

Authors
Tavares, PC; Henriques, PR; Gomes, EF;

Publication
CSEDU 2017 - Proceedings of the 9th International Conference on Computer Supported Education, Volume 1, Porto, Portugal, April 21-23, 2017.

Abstract

2016

Automatic Classification of Anuran Sounds Using Convolutional Neural Networks

Authors
Colonna, J; Peet, T; Ferreira, CA; Jorge, AM; Gomes, EF; Gama, J;

Publication
Proceedings of the Ninth International C* Conference on Computer Science & Software Engineering, C3S2E '16, Porto, Portugal, July 20-22, 2016

Abstract
Anurans (frogs or toads) are closely related to the ecosystem and they are commonly used by biologists as early indicators of ecological stress. Automatic classification of anurans, by processing their calls, helps biologists analyze the activity of anurans on larger scale. Wireless Sensor Networks (WSNs) can be used for gathering data automatically over a large area. WSNs usually set restrictions on computing and transmission power for extending the network's lifetime. Deep Learning algorithms have gathered a lot of popularity in recent years, especially in the field of image recognition. Being an eager learner, a trained Deep Learning model does not need a lot of computing power and could be used in hardware with limited resources. This paper investigates the possibility of using Convolutional Neural Networks with Mel-Frequency Cepstral Coefficients (MFCCs) as input for the task of classifying anuran sounds. © 2016 ACM.

Supervised
thesis

2020

Identificação automática de aves a partir de áudio

Author
SILVESTRE DANIEL DIAS CARVALHO

Institution
IPP-ISEP

2019

Análise e previsão de acidentes rodoviários usando data mining

Author
BRUNO MIGUEL FERREIRA TEIXEIRA

Institution
IPP-ISEP

2018

Deteção de arritmias cardíacas em eletrocardiogramas usando deep learning

Author
GABRIEL MOREIRA DA ROCHA

Institution
IPP-ISEP

2018

Ferramenta de Data Mining para Dados Educacionais

Author
DIOGO MANUEL PEREIRA VIEIRA

Institution
IPP-ISEP

2018

Desenvolvimento de aplicação móvel multiplataforma (Apache Cordova vs Xamarin)

Author
DIOGO MIGUEL RODRIGUES E SILVA

Institution
IPP-ISEP