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Books and Theses
- 2017
[b1]Felipe Azevedo Pinage:
Handling Concept Drift Based on Data Similarity and Dynamic Classifier Selection. Federal University of Amazonas, Manaus, Brazil, 2017
Journal Articles
- 2023
- [j4]Fabrício Ceschin
, Marcus Botacin, Heitor Murilo Gomes, Felipe Azevedo Pinage, Luiz S. Oliveira, André Grégio:
Fast & Furious: On the modelling of malware detection as an evolving data stream. Expert Syst. Appl. 212: 118590 (2023) - 2020
- [j3]Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Gama:
A drift detection method based on dynamic classifier selection. Data Min. Knowl. Discov. 34(1): 50-74 (2020) - 2018
- [j2]Fabricio Ceschin, Felipe Azevedo Pinage, Marcos A. Castilho, David Menotti, Luiz S. Oliveira, Andre Gregio:
The Need for Speed: An Analysis of Brazilian Malware Classifers. IEEE Secur. Priv. 16(6): 31-41 (2018) - 2016
- [j1]Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Manuel Portela da Gama:
Classification systems in dynamic environments: an overview. WIREs Data Mining Knowl. Discov. 6(5): 156-166 (2016)
Conference and Workshop Papers
- 2015
- [c3]Felipe Azevedo Pinage, Eulanda Miranda dos Santos:
A Dissimilarity-Based Drift Detection Method. ICTAI 2015: 1069-1076 - 2013
- [c2]Felipe Azevedo Pinage, José Reginaldo H. Cavalho, José P. Queiroz-Neto:
Visual-based Natural Landmark Tracking Method to Support UAV Navigation over Rain Forest Areas. VISAPP (2) 2013: 416-419 - 2012
- [c1]Felipe Azevedo Pinage, José Reginaldo Hughes Carvalho, José Pinheiro de Queiroz Neto:
Natural Landmark Tracking Method to Support UAV Navigation over Rain Forest Areas. SBESC 2012: 105-110
Informal and Other Publications
- 2022
- [i1]Fabrício Ceschin, Marcus Botacin, Heitor Murilo Gomes, Felipe Azevedo Pinage, Luiz S. Oliveira, André Grégio:
Fast & Furious: Modelling Malware Detection as Evolving Data Streams. CoRR abs/2205.12311 (2022)
Coauthor Index
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