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1. ALBERTON, B.; ET AL. Leafing Patterns and Drivers across Seasonally Dry Tropical Communities. Remote Sensing, v. 11(19), 2267, 2019.

2. CACEFFO, RICARDO; EDUARDO VALLE; RICKSON MESQUITA; RODOLFO DE AZEVEDO. Assessment of Predictive Power of The Felder & Silverman Learning Styles Model on Students? Performance in an Introductory Physics Course. European Journal of Physics Education, v. 10, p. 1-22, 2019.

3. CAVALCANTE, CRISTINA C. B.; MASCHIO, CÉLIO; SANTOS, ANTONIO ALBERTO; SCHIOZER, DENIS; ROCHA, ANDERSON. A continuous learning algorithm for history matching. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v. 85, p. 543-568, 2019.

4. DOS SANTOS, C.; ET AL. Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region. Remote Sensing, v. 11(3), 334, 2019.
FERREIRA, ALEXANDRE; CARVALHO, TIAGO; ANDALO, FERNANDA A.; ROCHA, ANDERSON. Counteracting the contemporaneous proliferation of digital forgeries and fake news. ANAIS DA ACADEMIA BRASILEIRA DE CIÊNCIAS (ONLINE), v. 91, p. e20180149, 2019.

5. FERREIRA, ANSELMO; FELIPUSSI, SIOVANI C.; PIRES, Ramon; AVILA, SANDRA ; SANTOS, GEISE ; LAMBERT, JORGE ; HUANG, Jiwu ; ROCHA, ANDERSON . Eyes in the Skies: A Data-Driven Fusion Approach to Identifying Drug Crops From Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 12, p. 4773-4786, 2019.

6. GOMES, L.; TORRES, R.; AND CÔRTES, M. Bug report severity level prediction in open source software: A survey and research opportunities. Information & Software Technology, v. 115, p. 58-78, 2019.
DOURADO, I.; PEDRONETTE, D.; AND TORRES, R. Unsupervised graph-based rank aggregation for improved retrieval. Information Processing and Management v. 56(4), p. 1260-1279, 2019.

7. DOURADO, I.; GALANTE, R.; GONÇALVES, M.; AND TORRES, R. Bag of textual graphs (BoTG): A general graph-based text representation model. Journal of the Association for Information Science and Technology, v. 70(8), p. 817-829, 2019.

8. KUEHLKAMP, A.; PINTO, A.; ROCHA, A.; BOWYER, K. W.; AND CZAJKA, A. Ensemble of multi-view learning classifiers for cross-domain iris presentation attack detection. IEEE Transactions on Information Forensics and Security, 14(6):1419–1431, June 2019.

9. OLIVEIRA, ALBERTO; OAKLEY, ERIC; DA SILVA TORRES, RICARDO; ROCHA, ANDERSON. Relevance prediction in similarity-search systems using extreme value theory. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 60, p. 236-249, 2019.

10. MENDES JUNIOR, PEDRO RIBEIRO; BONDI, LUCA; BESTAGINI, PAOLO; TUBARO, STEFANO; ROCHA, ANDERSON. An In-Depth Study on Open-Set Camera Model Identification. IEEE Access, v. 7, p. 180713-180726, 2019.

11. MENINI, N.; ET AL. A Soft Computing Framework for Image Classification Based on Recurrence Plots. IEEE Geoscience and Remote Sensing Letters, v. 16(2), p. 320-324, 2019.

12. MUÑOZ, J.; GONÇALVES, M.; DIAS, Z.; AND TORRES, R. Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search. Pattern Recognition, v. 96, 2019.

13. NOGUEIRA, K.; ET AL. Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks. IEEE Geoscience and Remote Sensing Letters, v. 16(10), p. 1665-1669, 2019.

14. PEDRONETTE, D.; VALEM, L.; ALMEIDA, J.; AND TORRES, R. Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking. IEEE Transactions on Image Processing, V. 28(12), P. 5824-5838, 2019.

15. PIRES, RAMON; AVILA, SANDRA; WAINER, JACQUES; VALLE, EDUARDO; ABRAMOFF, MICHAEL D.; ROCHA, ANDERSON. A Data-driven Approach to Referable Diabetic Retinopathy Detection. ARTIFICIAL INTELLIGENCE IN MEDICINE, v. 96, p. 93-106, 2019.

16. RODRIGUES, D.; MOURA, F.; CUNHA, S.; AND TORRES, R. “Graph visual rhythms in temporal network analyses,” GraphIcal Models, v. 103, 2019.

17. VALLE, EDUARDO; FORNACIALI, MICHEL; MENEGOLA, AFONSO; TAVARES, JULIA; VASQUES BITTENCOURT, FLÁVIA ; LI, LIN TZY; AVILA, SANDRA . Data, Depth, and Design: Learning Reliable Models for Skin Lesion Analysis. NEUROCOMPUTING, v. 383, p. 303-313, 2019.

18. WERNECK, R.; RAVEAUX, R.; TABBONE, S.; AND TORRES, R. Learning cost function for graph classification with open-set methods. Pattern Recognition Letters, v. 128, p. 8-15, 2019.

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