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+% ======================================================================
+% Referências -- Artigo: Classificação de Imagens RGB com SVM
+% e Atributos Extraídos por Transfer Learning (MobileNetV2)
+% Curso CEAO-802 | Instituto Tecnológico de Aeronáutica
+% ======================================================================
+
+% -------- Referência-base do trabalho (galoa / SBSR 2023) --------
+
+@inproceedings{lacerda2023,
+  author    = {Lacerda, Marielcio Gon{\c{c}}alves and
+               Habermann, Mateus and
+               Lacerda, Camila Souza dos Anjos and
+               Roos, Daniel Rodrigues and
+               K{\"o}rting, Thales Sehn and
+               Kux, Hermann Johann Heinrich},
+  title     = {Classifica{\c{c}}{\~a}o de Imagens Utilizando Imagens {RGB}
+               e Termal Obtidas por {ARPS} de Pequeno Porte},
+  booktitle = {Anais do XX Simp{\'o}sio Brasileiro de Sensoriamento Remoto (SBSR)},
+  year      = {2023},
+  address   = {Florian{\'o}polis, SC, Brasil},
+  pages     = {3368--3371},
+  url       = {https://proceedings.science/p/164924}
+}
+
+% -------- Teoria SVM --------
+
+@book{vapnik1995,
+  author    = {Vapnik, Vladimir N.},
+  title     = {The Nature of Statistical Learning Theory},
+  publisher = {Springer},
+  address   = {New York},
+  year      = {1995},
+  doi       = {10.1007/978-1-4757-2440-0}
+}
+
+@article{cortes1995,
+  author    = {Cortes, Corinna and Vapnik, Vladimir},
+  title     = {Support-Vector Networks},
+  journal   = {Machine Learning},
+  volume    = {20},
+  number    = {3},
+  pages     = {273--297},
+  year      = {1995},
+  doi       = {10.1007/BF00994018}
+}
+
+% -------- SVM em Sensoriamento Remoto --------
+
+@article{melgani2004,
+  author    = {Melgani, Farid and Bruzzone, Lorenzo},
+  title     = {Classification of Hyperspectral Remote Sensing Images
+               with Support Vector Machines},
+  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
+  volume    = {42},
+  number    = {8},
+  pages     = {1778--1790},
+  year      = {2004},
+  doi       = {10.1109/TGRS.2004.831865}
+}
+
+@article{campsvalls2005,
+  author    = {Camps-Valls, Gustavo and Bruzzone, Lorenzo},
+  title     = {Kernel-Based Methods for Hyperspectral Image Classification},
+  journal   = {{IEEE} Transactions on Geoscience and Remote Sensing},
+  volume    = {43},
+  number    = {6},
+  pages     = {1351--1362},
+  year      = {2005},
+  doi       = {10.1109/TGRS.2005.846154}
+}
+
+% -------- Transfer Learning / Redes Convolucionais --------
+
+@inproceedings{sandler2018,
+  author    = {Sandler, Mark and Howard, Andrew and Zhu, Menglong and
+               Zhmoginov, Andrey and Chen, Liang-Chieh},
+  title     = {{MobileNetV2}: Inverted Residuals and Linear Bottlenecks},
+  booktitle = {Proceedings of the {IEEE} Conference on Computer Vision
+               and Pattern Recognition (CVPR)},
+  year      = {2018},
+  pages     = {4510--4520},
+  doi       = {10.1109/CVPR.2018.00474}
+}
+
+@article{cheng2020,
+  author    = {Cheng, Gong and Xie, Xingxing and Han, Junwei and
+               Guo, Lei and Xia, Gui-Song},
+  title     = {Remote Sensing Image Scene Classification Meets Deep Learning:
+               Challenges, Methods, Benchmarks, and Opportunities},
+  journal   = {{IEEE} Journal of Selected Topics in Applied Earth Observations
+               and Remote Sensing},
+  volume    = {13},
+  pages     = {3735--3756},
+  year      = {2020},
+  doi       = {10.1109/JSTARS.2020.3005403}
+}
+
+% -------- Random Forest --------
+
+@article{breiman2001,
+  author  = {Breiman, Leo},
+  title   = {Random Forests},
+  journal = {Machine Learning},
+  volume  = {45},
+  number  = {1},
+  pages   = {5--32},
+  year    = {2001},
+  doi     = {10.1023/A:1010933404324}
+}
+
+% -------- Linguagem R --------
+
+@manual{r_core,
+  title        = {R: A Language and Environment for Statistical Computing},
+  author       = {{R Core Team}},
+  organization = {R Foundation for Statistical Computing},
+  address      = {Vienna, Austria},
+  year         = {2024},
+  url          = {https://www.R-project.org/}
+}