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ORCIDVinícius M. A. de Souza
Person information
- affiliation: University of São Paulo, Institute of Mathematics and Computer Science, Brazil
- affiliation: State University of Maringá, Informatics Department, Brazil
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Books and Theses
- 2016
[b1]Vinícius Mourão Alves de Souza:
Classification of non-stationary data stream with application in sensors for insect identification. University of São Paulo, Brazil, 2016
Journal Articles
- 2025
- [j15]Vinícius M. A. de Souza
, Patrickerson S. Veiga, André G. R. Ribeiro:
Visemble: A fast ensemble approach for time series classification with multiple visual representations. Knowl. Based Syst. 309: 112864 (2025) - 2024
- [j14]Lucas G. M. Castro, Henrique V. Costa, Vinícius M. A. de Souza:
Time-Series Mining Approaches for Malaria Vector Prediction On Mid-Infrared Spectroscopy Data. Data Sci. J. 23 (2024) - 2023
- [j13]Felipe Tomazelli Lima, Vinícius M. A. de Souza:
A Large Comparison of Normalization Methods on Time Series. Big Data Res. 34: 100407 (2023) - 2022
- [j12]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions. IEEE Access 10: 78022-78043 (2022) - [j11]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Arpita Seth, Indre Zliobaite, Gustavo E. A. P. A. Batista:
Hierarchical classification of pollinating flying insects under changing environments. Ecol. Informatics 70: 101751 (2022) - [j10]Sheng Zhong, Vinícius M. A. de Souza, Abdullah Mueen:
Combining Filtering and Cross-Correlation Efficiently for Streaming Time Series. ACM Trans. Knowl. Discov. Data 16(5): 100:1-100:24 (2022) - 2021
- [j9]Vinícius M. A. de Souza, Antonio Rafael Sabino Parmezan, Farhan Asif Chowdhury, Abdullah Mueen:
Efficient unsupervised drift detector for fast and high-dimensional data streams. Knowl. Inf. Syst. 63(6): 1497-1527 (2021) - 2020
- [j8]Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Challenges in benchmarking stream learning algorithms with real-world data. Data Min. Knowl. Discov. 34(6): 1805-1858 (2020) - 2019
- [j7]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model. Inf. Sci. 484: 302-337 (2019) - 2018
- [j6]Vinícius M. A. de Souza:
Asphalt pavement classification using smartphone accelerometer and Complexity Invariant Distance. Eng. Appl. Artif. Intell. 74: 198-211 (2018) - [j5]Vinícius M. A. de Souza, Rafael Giusti, Antonio J. L. Batista:
Asfault: A low-cost system to evaluate pavement conditions in real-time using smartphones and machine learning. Pervasive Mob. Comput. 51: 121-137 (2018) - 2017
- [j4]Vinícius Mourão Alves de Souza, Rafael Geraldeli Rossi, Gustavo E. A. P. A. Batista, Solange O. Rezende:
Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data. Intell. Data Anal. 21(5): 1061-1095 (2017) - 2015
- [j3]Diego Furtado Silva, Vinícius M. A. de Souza, Daniel P. W. Ellis, Eamonn J. Keogh, Gustavo E. A. P. A. Batista:
Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods. J. Intell. Robotic Syst. 80(Supplement-1): 313-330 (2015) - 2014
- [j2]Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Oben Moses Tataw, Vinícius M. A. de Souza:
CID: an efficient complexity-invariant distance for time series. Data Min. Knowl. Discov. 28(3): 634-669 (2014) - 2013
- [j1]Vinícius Mourão Alves de Souza, Valéria Delisandra Feltrim:
A coherence analysis module for SciPo: providing suggestions for scientific abstracts written in Portuguese. J. Braz. Comput. Soc. 19(1): 59-73 (2013)
Conference and Workshop Papers
- 2024
- [c30]Henrique V. Costa, André G. R. Ribeiro, Vinícius M. A. de Souza:
Fusion of Image Representations for Time Series Classification with Deep Learning. ICANN (6) 2024: 235-250 - [c29]Jonas Krause, Alexandre C. A. Beiruth, Jean Paul Barddal, Alceu S. Britto Jr., Vinícius M. A. de Souza:
Fuels Demand Forecasting: Identifying Leading Feature Sets, Prediction Strategy, and Regressors. ICMLA 2024: 957-962 - [c28]Rodrigo Kruger, Abdullah Mueen, Vinícius M. A. de Souza:
Peak Prediction in Time Series: Comparing Approaches for Energy High-Load Prediction. IJCNN 2024: 1-8 - 2023
- [c27]Sheng Zhong, Vinícius M. A. de Souza, Glenn Eli Baker, Abdullah Mueen:
Online Few-Shot Time Series Classification for Aftershock Detection. KDD 2023: 5707-5716 - 2022
- [c26]Rodrigo H. Zanella, Lucas A. de Castro Coelho, Vinícius M. A. de Souza:
TS-DENSE: Time Series Data Augmentation by Subclass Clustering. ICPR 2022: 1800-1806 - [c25]M. Ashraf Siddiquee, Vinícius M. A. de Souza, Glenn Eli Baker, Abdullah Mueen:
Septor: Seismic Depth Estimation Using Hierarchical Neural Networks. KDD 2022: 3889-3897 - 2021
- [c24]Md. Parvez Mollah, Vinícius M. A. de Souza, Abdullah Mueen:
Multi-way Time Series Join on Multi-length Patterns. ICDM 2021: 429-438 - 2020
- [c23]Vinícius M. A. de Souza, Farhan Asif Chowdhury, Abdullah Mueen:
Unsupervised Drift Detection on High-speed Data Streams. IEEE BigData 2020: 102-111 - [c22]Sheng Zhong, Vinícius M. A. de Souza, Abdullah Mueen:
FilCorr: Filtered and Lagged Correlation on Streaming Time Series. ICDM 2020: 1436-1441 - 2019
- [c21]Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems. ICTAI 2019: 1633-1637 - 2018
- [c20]Vinícius M. A. de Souza, Tiago Pinho da Silva, Gustavo E. A. P. A. Batista:
Evaluating Stream Classifiers with Delayed Labels Information. BRACIS 2018: 408-413 - [c19]Tiago Pinho da Silva, Vinícius Mourão Alves de Souza, Gustavo Enrique De Almeida Prado Alves Batista, Heloisa de Arruda Camargo:
A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels. CIARP 2018: 287-295 - [c18]Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Towards Hierarchical Classification of Data Streams. CIARP 2018: 314-322 - 2017
- [c17]Vinícius M. A. de Souza, Everton Alvares Cherman, Rafael Geraldeli Rossi, Rafael A. Souza:
Towards Automatic Evaluation of Asphalt Irregularity Using Smartphone's Sensors. IDA 2017: 322-333 - 2016
- [c16]Vinícius M. A. de Souza:
Identifying Aedes aegypti Mosquitoes by Sensors and One-Class Classifiers. CIARP 2016: 10-18 - 2015
- [c15]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista, João Gama:
Classification of Evolving Data Streams with Infinitely Delayed Labels. ICMLA 2015: 214-219 - [c14]Yu Qi, Goktug T. Cinar, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Yueming Wang, José C. Príncipe:
Effective insect recognition using a stacked autoencoder with maximum correntropy criterion. IJCNN 2015: 1-7 - [c13]Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
An experimental analysis on time series transductive classification on graphs. IJCNN 2015: 1-8 - [c12]Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Nilson E. Souza-Filho:
Automatic classification of drum sounds with indefinite pitch. IJCNN 2015: 1-8 - [c11]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Music Shapelets for Fast Cover Song Recognition. ISMIR 2015: 441-447 - [c10]Vinícius M. A. de Souza, Diego Furtado Silva, João Gama, Gustavo E. A. P. A. Batista:
Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency. SDM 2015: 873-881 - 2014
- [c9]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Extracting Texture Features for Time Series Classification. ICPR 2014: 1425-1430 - [c8]Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study. ICPR 2014: 3780-3785 - 2013
- [c7]Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista:
Classification of Data Streams Applied to Insect Recognition: Initial Results. BRACIS 2013: 76-81 - [c6]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
Time Series Classification Using Compression Distance of Recurrence Plots. ICDM 2013: 687-696 - [c5]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Daniel P. W. Ellis:
Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps. ICMLA (1) 2013: 99-104 - [c4]Vinícius M. A. de Souza, Valéria Delisandra Feltrim:
Uma Investigação sobre Algoritmos de Diferentes Abordagens de Aprendizado Supervisionado na Classificação de Papéis Retóricos em Resumos Científicos (Investigating Algorithms from Different Approaches of Supervised Learning for the Classification of Rhetorical Roles in Scientific Abstracts) [in Portuguese]. STIL 2013 - 2012
- [c3]Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Rafael Giusti:
Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies. IBERAMIA 2012: 241-250 - 2011
- [c2]Vinícius Mourão Alves de Souza, Valéria Delisandra Feltrim:
Automatic Analysis of Semantic Coherence in Academic Abstracts Written in Portuguese. IJCNLP 2011: 1144-1152 - [c1]Vinícius Mourão Alves de Souza, Valéria Delisandra Feltrim:
Análise automática de aspectos relacionados a coerência semântica em resumos acadêmicos (Automatic Analysis of Semantic Coherence Aspects in Academic Abstracts) [in Portuguese]. STIL 2011
Informal and Other Publications
- 2021
- [i2]Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista:
An Open-Source Tool for Classification Models in Resource-Constrained Hardware. CoRR abs/2105.05983 (2021) - 2020
- [i1]Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista:
Challenges in Benchmarking Stream Learning Algorithms with Real-world Data. CoRR abs/2005.00113 (2020)
Coauthor Index
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