Journals

See below a list of the journal publications of Recod.ai in the last 5 years. For more details and a complete list, check our latest yearly report.


2021

  1. CIRINO, CAROLINA; GOBATTO, CLAUDIO A.; PINTO, ALLAN S.; TORRES, RICARDO S; HARTZ, CHARLINI S.; AZEVEDO, PAULO H. S. M.; MORENO, MARLENE A.; AND MANCHADO-GOBATTO, FÚLVIA B. Complex network model indicates a positive effect of inspiratory muscles pre-activation on performance parameters in a judo match. Scientific Reports, 11(1):11148, May 2021.
  2. DELAFIORI, JEANY; NAVARRO, LUIZ CLÁUDIO; SICILIANO, RINALDO FOCACCIA; DE MELO, GISELY CARDOSO; BUSANELLO, ESTELA NATACHA BRANDT; NICOLAU, JOSÉ CARLOS; SALES, GEOVANA MANZAN; DE OLIVEIRA, ARTHUR NOIN; VAL, FERNANDO FONSECA ALMEIDA; DE OLIVEIRA, DIOGO NOIN; EGUTI, ADRIANA; DOS SANTOS, LUIZ AUGUSTO; DALÇÓQUIO, TALIA FALCÃO; BERTOLIN, ADRIADNE JUSTI; ABREU-NETTO, REBECA LINHARES; SALSOSO, ROCIO; BAÍA-DA-SILVA, DJANE; MARCONDES-BRAGA, FABIANA G; SAMPAIO, VANDERSON SOUZA; JUDICE, CARLA CRISTINA; COSTA, FABIO TRINDADE MARANHÃO; DURÁN, NELSON; PERROUD, MAURICIO WESLEY; SABINO, ESTER CERDEIRA; LACERDA, MARCUS VINICIUS GUIMARÃES, et al. ; Covid-19 Automated Diagnosis and Risk Assessment through Metabolomics and Machine Learning. ANALYTICAL CHEMISTRY, v. 93, p. 2471-2479, 2021.
  3. ESMAEL, A.; DA SILVA, H.; JI, T.; AND TORRES, R. “Non-Technical Loss Detection in Power Grid Using Information Retrieval Approaches: A Comparative Study,” IEEE Access 9: 40635-40648, 2021.
  4. RODRIGUES, C. M.; SORIANO-VARGAS, A.; LAVI, B.; ROCHA, A.; & DIAS, Z. (2021). Manifold Learning for Real-World Event Understanding. IEEE Transactions on Information Forensics and Security, 16, 2957-2972.
  5. RODRÍGUEZ SANTANDER, MIGUEL; HERNÁNDEZ ALBARRACÍN, JUAN; RAMÍREZ RIVERA, ADÍN. On the Pitfalls of Learning with Limited Data: A Facial Expression Recognition Case Study. EXPERT SYSTEMS WITH APPLICATIONS, v. V, p. 114991, 2021.
  6. ROLLMANN, K.; SORIANO-VARGAS, A.; ALMEIDA, F.; DAVOLIO, A.; SCHIOZER, D. J.; & ROCHA, A. (2021). Convolutional Neural Network Formulation to Compare 4-D Seismic and Reservoir Simulation Models. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, p. 1 – 14, 2021.
  7. SORIANO-VARGAS, A.; WERNECK, R.; MOURA, R.; MENDES JÚNIOR, P.; PRATES, R.; CASTRO, M.; GONÇALVES, M; HOSSAIN, M.; ZAMPIERI, M.; FERREIRA, A.; DAVÓLIO, A.; HAMANN, B.; SCHIOZER, D. J.; ROCHA, A. (2021). A visual analytics approach to anomaly detection in hydrocarbon reservoir time series data. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, p. 108988, 2021.

2020

  1. ALBARRACIN, J.; OLIVEIRA, R.; HIROTA, M.; DOS SANTOS, J.; AND TORRES, R. “A Soft Computing Approach for Selecting and Combining Spectral Bands,”  Remote Sensing 12(14): 2267, 2020.
  2. ALMEIDA, ALEXANDRE G.; MERLIN, MURILO; PINTO, ALLAN; TORRES, RICARDO DA S.;  AND CUNHA, SERGIO A. Performance-level indicators of male elite handball teams. International Journal of Performance Analysis in Sport, 20(1):1–9, November 2020.
  3. ALMEIDA, WALDIR R.; ANDALÓ, FERNANDA A.; PADILHA, RAFAEL; BERTOCCO, GABRIEL; DIAS, WILLIAM; TORRES, RICARDO DA S.; WAINER, JACQUES; ROCHA, ANDERSON. Detecting face presentation attacks in mobile devices with a patch-based CNN and a sensor-aware loss function. PLoS One, v. 15, p. e0238058-24, 2020.
  4. CARVALHO, LUIZ SÉRGIO F.; GIOPPATO, SILVIO; FERNANDEZ, MARTA D.; TRINDADE, BERNARDO C.; SILVA, JOSÉ CARLOS Q. E.; MIRANDA, REBECA G. S.; SOUZA, BETO J. R. M.; NADRUZ JUNIOR, W. ; AVILA, SANDRA; SPOSITO, ANDREI C. Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes. VALUE IN HEALTH, v. 23, p. 1570-1579, 2020.
  5. CAVALCANTE, CRISTINA C.B.; MASCHIO, CÉLIO; SCHIOZER, DENIS; ROCHA, ANDERSON. A stochastic learning-from-data approach to the history-matching problem. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v. 94, p. 103767, 2020.
  6. CÓRDOVA, M.; PINTO, A.; PEDRINI, H.; AND TORRES, R. D. S. “Pelee-Text++: A Tiny Neural Network for Scene Text Detection,” in IEEE Access, vol. 8, pp. 223172-223188, 2020.
  7. DIAS, D.; PINTO, A.; DIAS, U.; LAMPARELLI, R.; LE MAIRE, G.; AND TORRES, R. D. S. A multirepresentational fusion of time series for pixelwise classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13(1):4399–4409, July 2020.
  8. DIAS, D.; DIAS, U.; MENINI, N.; LAMPARELLI, R.; LE MAIRE, G.; AND TORRES, R. “Image-Based Time Series Representations for Pixelwise Eucalyptus Region Classification: A Comparative Study,” in IEEE Geoscience and Remote Sensing Letters, 17(8): 1450-1454, 2020.
  9. DIAS-AUDIBERT, FLÁVIA LUÍSA ; NAVARRO, LUIZ CLAUDIO ; DE OLIVEIRA, DIOGO NOIN ; DELAFIORI, JEANY ; MELO, CARLOS FERNANDO ODIR RODRIGUES ; GUERREIRO, TATIANE MELINA ; ROSA, FLÁVIA TRONCON ; PETENUCI, DIEGO LIMA ; WATANABE, MARIA ANGELICA EHARA ; VELLOSO, LICIO AUGUSTO ; ROCHA, ANDERSON REZENDE ; CATHARINO, RODRIGO RAMOS. Combining Machine Learning and Metabolomics to Identify Weight Gain Biomarkers. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, v. 8, p. 1-11, 2020.
  10. FADEL, S.; AND TORRES, R. “Neural relational inference for disaster multimedia retrieval,” in Multimedia Tools and Applications, 79(35-36): 26735-26746, 2020.
  11. FLORES CAMPANA, J. L.  ET AL., “On the Fusion of Text Detection Results: A Genetic Programming Approach,” in IEEE Access, vol. 8, pp. 81257-81270, 2020.
  12. FOLEGO, GUILHERME; WEILER, MARINA; CASSEB, R. F.; PIRES, RAMON; ROCHA, ANDERSON. Alzheimer’s Disease Detection Through Whole-Brain 3D-CNN MRI. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, v. 8, p. 1193-1207, 2020.
  13. IQBAL, MD TAUHID BIN; RYU, BYUNGYONG; RAMIREZ RIVERA, ADIN; MAKHMUDKHUJAEV, FARKHOD; CHAE, OKSAM; BAE, SUNG-HO. Facial Expression Recognition with Active Local Shape Pattern and Learned-Size Block Representations. IEEE Transactions on Affective Computing, v. V, p. 1-1, 2020.
  14. LI, HAOLIANG; WANG, SHIQI; HE, PEISONG; ROCHA, ANDERSON. Face Anti-Spoofing With Deep Neural Network Distillation. IEEE Journal of Selected Topics in Signal Processing, v. 14, p. 933-946, 2020.
  15. LIMA, ESTELA DE OLIVEIRA; NAVARRO, LUIZ CLAUDIO; MORISHITA, KAREN NODA; KAMIKAWA, CAMILA MIKA; RODRIGUES, RAFAEL GUSTAVO MARTINS; DABAJA, MOHAMED ZIAD; DE OLIVEIRA, DIOGO NOIN; DELAFIORI, JEANY; DIAS-AUDIBERT, FLÁVIA LUÍSA; RIBEIRO, MARTA DA SILVA; VICENTINI, ADRIANA PARDINI; ROCHA, ANDERSON; CATHARINO, RODRIGO RAMOS . Metabolomics and Machine Learning Approaches Combined in Pursuit for More Accurate Paracoccidioidomycosis Diagnoses. mSystems, v. 5, p. 1-12, 2020.
  16. PADILHA, RAFAEL; MAZINI, CAROLINE; ANDALO, FERNANDA ALCANTARA; BERTOCCO, GABRIEL; DIAS, ZANONI; ROCHA, ANDERSON. Forensic Event Analysis: From Seemingly Unrelated Data to Understanding. IEEE SECURITY & PRIVACY, v. 18, p. 23-32, 2020.
  17. PADILHA, RAFAEL; ANDALÓ, FERNANDA A.; BERTOCCO, GABRIEL; ALMEIDA, WALDIR R.; DIAS, WILLIAM; RESEK, THIAGO; TORRES, RICARDO DA S.; WAINER, JACQUES; ROCHA, ANDERSON. Two-tiered face verification with low-memory footprint for mobile devices. IET Biometrics, v. 9, p. 205-215, 2020.
  18. PINTO, A.; GOLDENSTEIN,  S.; FERREIRA, A.; CARVALHO, T.; PEDRINI, H.; AND ROCHA, A. Leveraging shape, reflectance and albedo from shading for face presentation attack detection. IEEE Transactions on Information Forensics and Security, 15:3347–3358, April 2020.
  19. QUISPE, R.; TTITO, D.; RAMÍREZ RIVERA, A.; PEDRINI, H. Multi-stream networks and ground-truth generation for crowd counting. International Journal of Electrical and Computer Engineering Systems, v. V, p. 1, 2020.
  20. RAMÍREZ RIVERA, A.; KHAN, A.; BEKKOUCH, I.; SHEIKH, T. Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation. IEEE Transactions on Neural Networks and Learning Systems, p. 1-11, 2020.
  21. ROCHA, ANDERSON. The Information Forensics and Security Technical Committee: Then, Now, and in the Future [In the Spotlight]. IEEE SIGNAL PROCESSING MAGAZINE, v. 37, p. 175-176, 2020.
  22. SANTOS, GEISE; PISANI, PAULO HENRIQUE; LEYVA, ROBERTO; LI, CHANG-TSUN; TAVARES, TIAGO; ROCHA, ANDERSON . Manifold learning for user profiling and identity verification using motion sensors. PATTERN RECOGNITION, v. 106, p. 107408-16, 2020.
  23. SANTOS, THIAGO T. ; DE SOUZA, LEONARDO L. ; DOS SANTOS, ANDREZA A. ; AVILA, SANDRA . Grape detection, segmentation, and tracking using deep neural networks and three-dimensional association. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 170, p. 105247, 2020.
  24. SILVA, EWERTON; TORRES, RICARDO DA S.; PINTO, ALLAN; LI, LIN TZY; VIANNA, JOSÉ EDUARDO S.; AZEVEDO, RODOLFO; AND GOLDENSTEIN, SIOME. Application-oriented retinal image models for computer vision. Sensors, 20(13):3746, July 2020
  25. SILVA, E.; TORRES, R.; ALBERTON, B.; MORELLATO, L.; AND SILVA, T. “A Change-Driven Image Foveation Approach for Tracking Plant Phenology,” Remote Sensing 12(9): 1409, 2020.
  26. SORIANO-VARGAS, A.; ROLLMANN, K.; ALMEIDA, F.; DAVOLIO, A.; HAMANN, B.; SCHIOZER, D. J.; & ROCHA, A. (2020). A synthetic case study of measuring the misfit between 4D seismic data and numerical reservoir simulation models through the Momenta Tree. Computers & Geosciences, 145, 104617.
  27. VERDE, SEBASTIANO; RESEK, Thiago; MILANI, SIMONE; ROCHA, ANDERSON . Ground-to-Aerial Viewpoint Localization via Landmark Graphs Matching. IEEE SIGNAL PROCESSING LETTERS, v. 27, p. 1490-1494, 2020.

2019

  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.
  5. 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.
  6. 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.
  7. 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.
  8. 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
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. RODRIGUES, D.; MOURA, F.; CUNHA, S.; AND TORRES, R. “Graph visual rhythms in temporal network analyses,” GraphIcal Models, v. 103, 2019.
  19. 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.
  20. 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.

2018

  1. ARAUJO, LUCAS M.; OLIVEIRA, FABÍOLA M. C.; FACCIPIERI, JORGE H.; COIMBRA, TIAGO A. A.; AVILA, SANDRA; TYGEL, MARTIN; BORIN, EDSON. Detecção de estruturas em dados sísmicos com Deep Learning. BOLETIM SBGF, v. 104, p. 18-21, 2018.
  2. CORDOVA NEIRA, MANUEL ALBERTO; MENDES JR., PEDRO RIBEIRO; ROCHA, ANDERSON; TORRES, RICARDO. Data-Fusion Techniques for Open-Set Recognition Problems. IEEE Access (ACCESS), To Appear, 2018.
  3. ESMAEL, A.; DOS SANTOS, J.; AND TORRES, R. On the ensemble of multiscale object-based classifiers for aerial images: a comparative study. Multimedia Tools and Applications, v. 77(19), p. 24565-24592, 2018.
  4. LI, HAOLIANG; HE, PEISONG; WANG, SHIQI; ROCHA, ANDERSON; JIANG, XINGHAO; KOT, ALEX C. Learning Generalized Deep Feature Representation for Face Anti-spoofing. IEEE Transactions on Information Forensics and Security (T.IFS), To Appear, 2018.
  5. MARIANO, G.; STAGGEMEIER, V.; MORELLATO, L.; AND TORRES, R. Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis. EcolOGICAL Informatics, v. 46, p. 19-35, 2018.
  6. MELO, CARLOS FERNANDO ODIR RODRIGUES NAVARRO, LUIZ CLAUDIO DE OLIVEIRA, DIOGO NOIN GUERREIRO, TATIANE MELINA LIMA, ESTELA DE OLIVEIRA DELAFIORI, JEANY DABAJA, MOHAMED ZIAD RIBEIRO, MARTA DA SILVA DE MENEZES, MAICO RODRIGUES, RAFAEL GUSTAVO MARTINS MORISHITA, KAREN NODA ESTEVES, CIBELE ZANARDI DE AMORIM, ALINE LOPES LUCAS AOYAGUI, CAROLINE TIEMI PARISE, PIERINA LORENCINI MILANEZ, GUILHERME PAIER DO NASCIMENTO, GABRIELA MANSANO RIBAS FREITAS, ANDRÉ RICARDO ANGERAMI, RODRIGO COSTA, FÁBIO TRINDADE MARANHÃO ARNS, CLARICE WEIS RESENDE, MARIANGELA RIBEIRO AMARAL, ELIANA JUNIOR, RENATO PASSINI RIBEIRO-DO-VALLE, CAROLINA C. , et al.; A Machine Learning Application Based in Random Forest for Integrating Mass Spectrometry-Based Metabolomic Data: A Simple Screening Method for Patients With Zika Virus. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, v. 6, p. 1-11, 2018.
  7. MOREIRA, DANIEL; AVILA, SANDRA; PEREZ, MAURICIO; MORAES, DANIEL; TESTONI, VANESSA; VALLE, EDUARDO; GOLDENSTEIN, SIOME; ROCHA, ANDERSON. Multimodal Data Fusion for Sensitive Scene Localization. Information Fusion, v. 45, p. 307-323, 2018.
  8. MOREIRA, D.; BHARATI, A.; BROGAN, J.; PINTO, A.; PAROWSKI, M.; BOWYER, K. W.; FLYNN, P. J.; ROCHA, A.; AND SCHEIRER, W. J. Image provenance analysis at scale. IEEE Transactions on Image Processing, 27(12):6109–6123, Dec 2018
  9. MOREIRA, DANIEL; AVILA, SANDRA; PEREZ, MAURICIO; MORAES, DANIEL ; TESTONI, VANESSA ; VALLE, EDUARDO ; GOLDENSTEIN, SIOME ; ROCHA, ANDERSON. Multimodal Data Fusion for Sensitive Scene Localization. Information Fusion, v. P99, p. 1-18, 2018.
  10. NAVARRO, LUIZ; NAVARRO, ALEXANDRE K.W.; ROCHA, ANDERSON, DAHAB, RICARDO. Connecting the Dots: Toward Accountable Machine-Learning Printer Attribution Methods. Journal of Visual Communication and Image Representation (JVCI), To Appear, 2018.
  11. NAVARRO, LUIZ; NAVARRO, ALEXANDRE K. W.; GREGIO, ANDRE; ROCHA, ANDERSON; DAHAB, RICARDO. Leveraging Ontologies and Machine-learning Techniques for Malware Analysis into Android Permissions Ecosystems. COMPUTERS & SECURITY, v. 78, p. 429-453, 2018.
  12. NOGUEIRA, K.; ET AL. Exploiting ConvNet Diversity for Flooding Identification. IEEE Geoscience and Remote Sensing Letters, v. 15(9), p. 1446-1450, 2018.
  13. PEREIRA, LUÍS A. M.; TORRES, RICARDO DA SILVA. Semi-Supervised Transfer Subspace for Domain Adaptation. PATTERN RECOGNITION, v. 75, p. 235-249, 2018.
  14. ROCHA, ANDERSON; LI, SHUJUN; KUO, C.-C. JAY; PIVA, ALESSANDRO; HUANG, JIWU. Data-driven multimedia forensics and security. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 55, p. 447-448, 2018.
  15. RODRIGUES MELO, CARLOS FERNANDO; NAVARRO, LUIZ CLAUDIO; OLIVEIRA, DIOGO NOIN; GUERREIRO, TA- TIANE MELINA; LIMA, ESTELA DE OLIVEIRA; DELAFIORI, JEANY; DABAJA, MOHAMED ZIAD; RIBEIRO, MARTA DA SILVA; DE MENEZES, MAICO; MARTINS RODRIGUES, RAFAEL GUSTAVO; MORISHITA, KAREN NODA; ESTEVES, CIBELE ZANARDI; DE AMORIN, ALINE LOPES LUCAS; AOYAGUI, CAROLINE TIEMI; PARISE, PIERINA LORENCINI; MILANEZ, GUILHERME PAIER; NASCIMENTO, GABRIELA; FREITAS, ANDR ́E RICARDO RIBAS; ANGERAM, RODRIGO; COSTA, F ́ABIO TRINDADE MARANH ̃AO; WEIS ARNS, CLARICE; RESENDE, MARIANGELA RIBEIRO; ELIANA AMARAL; PASSINO JR, RENATO; RIBEIRO-DO-VALLE, CAROLINA C.; MILANEZ, HELAINE; MORETTI, MARIA LUIZA; PROENCA-MODENA, JOSE LUIZ; AVILA, SANDRA; ROCHA, ANDERSON; AND CATHARINO, RODRIGO RAMOS. A Machine Learning Application Based in Random Forest for Integrating Mass Spectrometry-Based Metabolomic Data: A Simple Screening Method for Patients With Zika Virus. Frontiers in Bioengineering and Biotechnology (FRONTIERS), To Appear, 2018.
  16. SEABRA OLIVEIRA, DANIELA; EPSTEIN, JEREMY; KUROSE, JAMES; ROCHA, ANDERSON . Cybersecurity and Privacy Issues in Brazil: Back, Now, and Then [Guest Editors’ Introduction]. IEEE SECURITY & PRIVACY, v. 16, p. 10-12, 2018.
  17. SHEN, BINGYU; FORSTALL, CHRISTOPHER W.; ROCHA, ANDERSON; SCHEIRER, WALTER J.. Practical Text Phylogeny for Real-World Settings. IEEE Access, v. 6, p. 41002-41012, 2018.
  18. SILVA, F. B.; WERNECK, R. O.; GOLDENSTEIN, S. K.; TABBONE, S.; TORRES, R. DA S. Graph-based Bag-of-Words for Classification. PATTERN RECOGNITION, v. 74, p. 266-285, 2018.
  19. VITORINO, PAULO; AVILA, SANDRA ELIZA FONTES; PEREZ, MAURICIO L.; ROCHA, ANDERSON. Leveraging Deep Neural Networks to Fight Child Pornography in the Age of Social Media. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 50, p. 303-313, 2018.
  20. WAINER, J; XAVIER, EDUARDO C. A Controlled Experiment on Python vs C for an Introductory Programming Course. ACM Transactions on Computing Education, v. 18, p. 1-16, 2018.
  21. WERNECK, RAFAEL DE OLIVEIRA; DE ALMEIDA, WALDIR RODRIGUES; STEIN, BERNARDO VECCHIA; PAZINATO, DANIEL VATANABE; JÚNIOR, PEDRO RIBEIRO MENDES; PENATTI, OTÁVIO AUGUSTO BIZETTO; ROCHA, ANDERSON; TORRES, RICARDO DA SILVA . Kuaa: A unified framework for design, deployment, execution, and recommendation of machine learning experiments. Future Generation Computer Systems-The International Journal of eScience, v. 78, p. 59-76, 2018.

2017

  1. ANDALÓ, F. A. ; TAUBIN, G. ; GOLDENSTEIN, S. PSQP: Puzzle Solving by Quadratic Programming. IEEE Transactions on Pattern Analysis and Machine Intelligence. v. 39, p. 385-396, 2017.
  2. NETO, L. B. ; GRIJALVA, F. ; MAIKE, V. ; MARTINI, L. C. ; FLORENCIO, D. ; BARANAUSKAS, C. ; ROCHA, A. ; GOLDENSTEIN, S. A Kinect-Based Wearable Face Recognition System to Aid Visually Impaired Users. IEEE Transactions on Human-Machine Systems. v. 47, p. 52-64, 2017.
  3. ROCHA, A. ; SCHEIRER, W. J. ; FORSTALL, C. W. ; CAVALCANTE, T. ; THEOPHILO, A. ; SHEN, B. ; CARVALHO, A. ; STAMATATOS, E. Authorship Attribution for Social Media Forensics. IEEE Transactions on Information Forensics and Security. v. 12, p. 5-33, 2017.
  4. RUPPERT, GUILHERME C.S. ; CHIACHIA, Giovani ; BERGO, FELIPE P.G. ; FAVRETTO, FERNANDA O. ; YASUDA, CLARISSA L. ; ROCHA, ANDERSON ; FALCÃO, Alexandre X. . Medical image registration based on watershed transform from greyscale marker and multi-scale parameter search. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, v. 5, p. 138-156, 2017.
  5. PEREZ, MAURICIO ; AVILA, SANDRA ; MORAES, Daniel ; TESTONI, Vanessa ; VALLE, Eduardo ; GOLDENSTEIN, Siome ; ROCHA, Anderson . Video pornography detection through deep learning techniques and motion information. Neurocomputing (Amsterdam), v. 230, p. 279-293, 2017.
  6. PIRES, Ramon ; AVILA, SANDRA ; JELINEK, Herbert F. ; Wainer, Jacques ; VALLE, Eduardo ; ROCHA, ANDERSON . Beyond Lesion-Based Diabetic Retinopathy: A Direct Approach for Referral. IEEE Journal of Biomedical and Health Informatics, v. 21, p. 193-200, 2017.
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