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English Information

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Authors
# Name
1 Renato Miyaji(re.miyaji@usp.br)
2 Felipe Almeida(felipe.valencia.almeida@usp.br)
3 Pedro Corrêa(pizzigatti@ieee.org)

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Reference
# Reference
1 Beery, S., Cole, E., Parker, J., Perona, P., and Winner, K. (2021). Species distribution modeling for machine learning practitioners: A review. In Proceedings of ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS) 2021.
2 GBIF (2024). Gbif | global biodiversity information facility. https://www.gbif.org/.Acesso em: 2024-05-14
3 Hamid, O. H. (2022). From model-centric to data-centric ai: A paradigm shift or rather a complementary approach? In Proceedings of 2022 8th International Conference on Information Technology Trends (ITT), pages 45–54. IEE.
4 Han, B., Yao, Q., Yu, X., Niu, G., Xu, M., Hu, W., Tsang, I., and Sugiyama, M (2018). Co-teaching: Robust training of deep neural networks with extremely noisy labels. In Proceeding of the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018).
5 ICMBio (2024). Portal da biodiversidade do instituto chico mendes de conservação da biodiversidade. https://portaldabiodiversidade.icmbio.gov.br/portal/. Acesso em: 2024-05-14.
6 Jiang, L., Zhou, Z., Leung, T., Li, L., and Fei-Fei, L. (2018). Mentornet: Learning datadriven curriculum for very deep neural networks on corrupted labels. In Proceeding of the International Conference on Machine Learning (ICML 2018).
7 Malach, E. and Shalev-Shwartz, S. (2017). Decoupling “when to update” from “how to update”. In Proceeding of the Conference on Neural Information Processing Systems (NIPS 2017)
8 Martin, S. T., Artaxo, P., Machado, L. A. T., Manzi, A. O., Souza, R. A. F. d., Schumacher, C., Wang, J., Andreae, M. O., Barbosa, H., Fan, J., et al. (2016). Introduction:observations and modeling of the green ocean amazon (goamazon2014/5). Atmospheric Chemistry and Physics, 16(8):4785 4797.
9 Martin, T. G., Kuhnert, P. M., Mengersen, K., and Possingham, H. P. (2005). The power of expert opinion in ecological models using bayesian methods: Impact of grazing on birds. Ecological Applications, 15:266–280.
10 Rew, J., Cho, U., and Hwang, E. (2021). A robust prediction model for species distribution using bagging ensembles with deep neural networks. Remote Sensing, 13(8):1945.
11 Vos, B., Jansen, G., and Isgum, I. (2023). Stochastic co-teaching for training neural networks with unknown levels of label noise. Scientifc Reports, 13(16875).
12 Miyaji, R. O., Almeida, F. V., Bauer, L. O., Ferrari, V., Corrêa, P. L. P., Rizzo, L. V., and Prakash, G. (2021). Spatial interpolation of air pollutant and meteorological variables in central amazonia. Data, 6(12).