SIRS Model Web Demo
Developed for the Complex Networks Course
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publications
Gated Recurrent Unit Hierarchical Architecture for Fundamental Stock Analysis and Forecast
Published in WAIAF (Workshop of Artificial Intelligence Applied to Finance) 2019, 2019
This work proposed a novel technique for fundamental analysis using GRU hierarchical models.
Recommended citation: Gabriel Adriano Melo, Paulo Marcelo Tasinaffo. "Gated Recurrent Unit Hierarchical Architecture for Fundamental Stock Analysis and Forecast." Presented at the Workshop of Artificial Intelligence Applied to Finance 2019 (WAIAF 2019).
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A MapReduce Based Approach for Circle Detection
Published in SciTePress, 2019
This paper proposes a parallel algorithm for circle detection using Hough Transform and MapReduce paradigm.
Recommended citation: Coelho, Mateus Menezes Azevedo, Dylan Nakandakari Sugimoto, Gabriel Adriano Melo, Vitor Venceslau Curtis, and Juliana de Melo Bezerra. "A MapReduce Based Approach for Circle Detection." In Proceedings of the 14th International Conference on Software Technologies (ICSOFT 2019), edited by Marten van Sinderen and Leszek A. Maciaszek, 454-459. Prague, Czech Republic: SciTePress, 2019. https://doi.org/10.5220/0007827604540459.
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A new approach to river flow forecasting: LSTM and GRU multivariate models
Published in IEEE Latin America Transactions, 2019
The monthly flow of a river was estimated using two recurrent neural networks techniques: Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU).
Recommended citation: G. Adriano de Melo, D. N. Sugimoto, P. M. Tasinaffo, A. H. Moreira Santos, A. M. Cunha and L. A. Vieira Dias, "A new approach to river flow forecasting: LSTM and GRU multivariate models," in IEEE Latin America Transactions, vol. 17, no. 12, pp. 1978-1986, December 2019, doi: 10.1109/TLA.2019.9011542.
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High Speed Marker Tracking for Flight Tests
Published in IEEE Latin America Transactions, 2022
We propose a new detecting and tracking model based on CNN, that uses fiducial markers.
Recommended citation: G. A. Melo, M. Máximo and P. A. Castro, "High Speed Marker Tracking for Flight Tests," in IEEE Latin America Transactions, vol. 20, no. 10, pp. 2237-2243, Oct. 2022, doi: 10.1109/TLA.2022.9885171.
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On the Undecidability of Artificial Intelligence Alignment: Machines that Halt
Published in ArXiv Preprint. Submitted for review in SciRep AI Alignment Collection, 2024
AI Alignment is undecidable. Nevertheless, there is an enumerable set of provenly aligned AIs that are constructed from a finite set of provenly aligned operations. We propose a halting constraint that guarantees that the AI model always reaches a terminal state in finite execution steps.
Recommended citation: de Melo, G. A., Maximo, M. R. O. D. A., Soma, N. Y., & de Castro, P. A. L. (2024). On the Undecidability of Artificial Intelligence Alignment: Machines that Halt. arXiv [Cs.AI]. Retrieved from http://arxiv.org/abs/2408.08995
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talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Introduction to Computer Vision
Graduate course, Instituto Tecnológico de Aeronáutica, Department of Computer Science, 2022
Notebooks: https://gam.dev/notebooks22.zip
Introduction to Computer Vision
Graduate course, Instituto Tecnológico de Aeronáutica, Department of Computer Science, 2023
Slides and Notebooks available at https://github.com/Gabrui/cm203. If you want the grading version (coding answers and additional tests) you can contact me.