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ORCIDMartha Dais Ferreira
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2020 – today
- 2022
[j4]Martha Dais Ferreira
, Gabriel Dias Cantareira, Rodrigo Fernandes de Mello, Fernando V. Paulovich:
Neural network training fingerprint: visual analytics of the training process in classification neural networks. J. Vis. 25(3): 593-612 (2022)- 2021
- [j3]Xuemin Yu, Martha Dais Ferreira, Fernando V. Paulovich:
Senti-COVID19: An Interactive Visual Analytics System for Detecting Public Sentiment and Insights Regarding COVID-19 From Social Media. IEEE Access 9: 126684-126697 (2021) - [i4]Leonardo Christino, Martha Dais Ferreira, Asal Jalilvand, Fernando V. Paulovich:
Explainable Patterns: Going from Findings to Insights to Support Data Analytics Democratization. CoRR abs/2101.08655 (2021) - [i3]Martha Dais Ferreira, Michal Malyska, Nicola Sahar, Riccardo Miotto, Fernando V. Paulovich, Evangelos E. Milios:
Active learning for medical code assignment. CoRR abs/2104.05741 (2021)
2010 – 2019
- 2019
- [j2]Christopher Dane Shulby, Martha Dais Ferreira, Rodrigo Fernandes de Mello, Sandra M. Aluísio:
Theoretical learning guarantees applied to acoustic modeling. J. Braz. Comput. Soc. 25(1): 1:1-1:12 (2019) - [c2]Christopher Dane Shulby, Martha Dais Ferreira, Rodrigo Fernandes de Mello, Sandra Maria Aluísio:
Robust Phoneme Recognition with Little Data. SLATE 2019: 4:1-4:11 - 2018
- [j1]Martha Dais Ferreira, Débora Cristina Corrêa, Luis Gustavo Nonato, Rodrigo Fernandes de Mello:
Designing architectures of convolutional neural networks to solve practical problems. Expert Syst. Appl. 94: 205-217 (2018) - 2017
- [c1]Christopher Dane Shulby, Martha Dais Ferreira, Rodrigo Fernandes de Mello, Sandra Maria Aluísio:
Acoustic Modeling Using a Shallow CNN-HTSVM Architecture. BRACIS 2017: 85-90 - [i2]Christopher Dane Shulby, Martha Dais Ferreira, Rodrigo Fernandes de Mello, Sandra Maria Aluísio:
Acoustic Modeling Using a Shallow CNN-HTSVM Architecture. CoRR abs/1706.09055 (2017) - [i1]Rodrigo Fernandes de Mello, Martha Dais Ferreira, Moacir Antonelli Ponti:
Providing theoretical learning guarantees to Deep Learning Networks. CoRR abs/1711.10292 (2017)
Coauthor Index
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