Pérez Hernández María Gabriela
Departamento de Informática y Ciencias de la Computación
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Oficina: 219
Ext: 4746
iD orcid.org/0000-0001-9628-2767
Estudios
  1. PhD en Informática en la Universidad Rey Juan Carlos de Madrid - España.
Líneas de investigación
  1. DICC-A1-L1 Inteligencia Artificial
  2. DICC-A1-L2 Machine learning
  3. DICC-A3-L2 Creación y Gestión del Software
  4. DICC-A4-L3 Sistemas de Información
Publicaciones
  1. Intriago-Pazmiño, M., Ibarra-Fiallo, J., Pérez-Hernández, M., Guzmán-Castillo, A., & Torres-Constante, E. (2022). Optic Disk Detection in Fundus Images of Retinopathy of Prematurity. Proceedings of the Future Technologies Conference (págs. 370-380). Springer International Publishing. doi: https://doi.org/10.1007/978-3-031-18344-7_25 
  2. Bastidas Fuertes, A., Pérez, M., & Meza Hormaza, J. (2023). Transpilers: A Systematic Mapping Review of Their Usage in Research and Industry. Applied Sciences 13, 3667. doi: https://doi.org/10.3390/app13063667 
  3. Díaz-Rodriguez, O. E., & Gabriela Perez Hernandez, M. (2020). Quality Event Log to Intention Mining: A Study Case. 2020 International Conference on Computer Science, Engineering and Applications, ICCSEA 2020. https://doi.org/10.1109/ICCSEA49143.2020.9132856
  4. Falconi, L., Perez, M., Aguilar, W., & Conci, A. (2020). Transfer learning and fine tuning in mammogram bi-rads classification. Proceedings - IEEE Symposium on Computer-Based Medical Systems, 2020-July, 475–480. https://doi.org/10.1109/CBMS49503.2020.00096
  5. Falconi, L. G., Perez, M., & Aguilar, W. G. (2019). Transfer Learning in Breast Mammogram Abnormalities Classification with Mobilenet and Nasnet. International Conference on Systems, Signals, and Image Processing, 2019-June, 109–114. https://doi.org/10.1109/IWSSIP.2019.8787295
  6. Bastidas, F. A., & Perez, M. (2018). A systematic review on Transpiler usage for Transaction-Oriented Applications. 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. https://doi.org/10.1109/ETCM.2018.8580312
  7. Diaz-Rodriguez, O. E., & Perez, M. (2018). Log Design for Storing Seismic Event Characteristics Using Process, Text, and Opinion Mining Techniques. 2018 5th International Conference on EDemocracy and EGovernment, ICEDEG 2018, 281–285. https://doi.org/10.1109/ICEDEG.2018.8372312
  8. Carrion, M., Santorum, M., Perez, M., & Aguilar, J. (2018). A participatory methodology for the design of serious games in the educational environment. 2017 Congreso Internacional de Innovacion y Tendencias En Ingenieria, CONIITI 2017 - Conference Proceedings, 2018-Janua, 1–6. https://doi.org/10.1109/CONIITI.2017.8273363
  9. Andres, B. F., & Perez, M. (2018). Transpiler-based architecture for multi-platform web applications. 2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017, 2017-January, 1–6. https://doi.org/10.1109/ETCM.2017.8247456
  10. Perez, M., Benalcazar, M. E., Tusa, E., Rivas, W., & Conci, A. (2018). Mammogram classification using back-propagation neural networks and texture feature descriptors. 2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017, 2017-Janua, 1–6. https://doi.org/10.1109/ETCM.2017.8247515
  11. Falconi, L. G., Perez, M., Aguilar, W. G., & Conci, A. (2020). Transfer learning and fine tuning in breast mammogram abnormalities classification on CBIS-DDSM database. Advances in Science, Technology and Engineering Systems, 5(2), 154–165. https://doi.org/10.25046/aj050220
  12. Souza Marques, R., Conci, A., Perez, M. G., Andaluz, V. H., & Mejia, T. M. (2016). An approach for automatic segmentation of thermal imaging in Computer Aided Diagnosis. IEEE Latin America Transactions, 14(4), 1856–1865. https://doi.org/10.1109/TLA.2016.7483526