Profesores

Benalcazar Palacios Marco Enrique
Departamento de Informática y Ciencias de la Computación
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Oficina: 203
Ext: 4706
iD orcid.org/0000-0002-5275-7262
Estudios
  1. Ingeniero en Electrónica y Telecomunicaciones en la Escuela Politécnica Nacional
  2. Máster en Tecnologías de los Sistemas de Energía Solar Fotovoltaica en Universidad Internacional de Andalucía
  3. Doctor en Ingeniería Electrónica en Universidad Nacional de Mar del Plata
Líneas de investigación
  1. DICC-A1-L1 Inteligencia Artificial
  2. DICC-A1-L2 Machine learning
  3. DICC-A1-L3 Modelado y simulación
  4. DICC-A4-L2 Computación centrada en el humano
Publicaciones
  1. Ona, A., Vimos, V., Benalcazar, M., & Cruz, P. J. (2020). Adaptive Non-linear Control for a Virtual 3D Manipulator. 2020 IEEE ANDESCON, ANDESCON 2020. https://doi.org/10.1109/ANDESCON50619.2020.9272154
  2. Nogales, R., & Benalcazar, M. (2019). Real-Time Hand Gesture Recognition Using the Leap Motion Controller and Machine Learning. 2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019. https://doi.org/10.1109/LA-CCI47412.2019.9037037
  3. YRamirez, F. E., Segura-Morales, M., & Benalcazar, M. (2018). Design of a Software Architecture and Practical Applications to Exploit the Capabilities of a Human Arm Gesture Recognition System. 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. https://doi.org/10.1109/ETCM.2018.8580267
  4. Valencia, E., Benalcazar, M., Saá, J. M., Magne, N., & Hidalgo, V. (2016). Design point analysis of a distributed propulsion system with boundary layer ingestion implemented in UAVs for agriculture in the Andean region. 52nd AIAA/SAE/ASEE Joint Propulsion Conference, 2016. https://doi.org/10.2514/6.2016-4799
  5. Vimos, V. H., Benalcázar, M., Oña, A. F., & Cruz, P. J. (2020). A Novel Technique for Improving the Robustness to Sensor Rotation in Hand Gesture Recognition Using sEMG. Advances in Intelligent Systems and Computing, 1078, 226–243. https://doi.org/10.1007/978-3-030-33614-1_16
  6. Nogales, R., & Benalcázar, M. (2020). Real-Time Hand Gesture Recognition Using KNN-DTW and Leap Motion Controller. Communications in Computer and Information Science, 1307, 91–103. https://doi.org/10.1007/978-3-030-62833-8_8
  7. Benalcazar, M. E., Gonzalez, J., Jaramillo-Yanez, A., Anchundia, C. E., Zambrano, P., & Segura, M. (2020). A Model for Real-Time Hand Gesture Recognition Using Electromyography (EMG), Covariances and Feed-Forward Artificial Neural Networks. 2020 IEEE ANDESCON, ANDESCON 2020. https://doi.org/10.1109/ANDESCON50619.2020.9271979
  8. Jaramillo-Yanez, A., Unapanta, L., & Benalcazar, M. E. (2019). Short-Term Hand Gesture Recognition using Electromyography in the Transient State, Support Vector Machines, and Discrete Wavelet Transform. 2019 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2019. https://doi.org/10.1109/LA-CCI47412.2019.9036757
  9. Dalton, L. A., Benalcazar, M. E., & Dougherty, E. R. (2018). Optimal clustering under uncertainty. PLoS ONE, 13(10). https://doi.org/10.1371/journal.pone.0204627
  10. Benalcazar, M. E., Motoche, C., Zea, J. A., Jaramillo, A. G., Anchundia, C. E., Zambrano, P., Segura, M., Benalcazar Palacios, F., & Perez, M. (2018). Real-time hand gesture recognition using the Myo armband and muscle activity detection. 2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017, 2017-Janua, 1–6. https://doi.org/10.1109/ETCM.2017.8247458
  11. Jaramillo, A. G., & Benalcazar, M. E. (2018). Real-time hand gesture recognition with EMG using machine learning. 2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017, 2017-January, 1–5. https://doi.org/10.1109/ETCM.2017.8247487
  12. 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-January, 1–6. https://doi.org/10.1109/ETCM.2017.8247515
  13. Benalcázar, M. E., Caraguay, Á. L. V, & López, L. I. B. (2020). A user-specific hand gesture recognition model based on feed-forward neural networks, emgs, and correction of sensor orientation. Applied Sciences (Switzerland), 10(23), 1–21. https://doi.org/10.3390/app10238604
  14. Jaramillo-Yánez, A., Benalcázar, M. E., & Mena-Maldonado, E. (2020). Real-time hand gesture recognition using surface electromyography and machine learning: A systematic literature review. Sensors (Switzerland), 20(9). https://doi.org/10.3390/s20092467
  15. Zea, J. A., & Benalcázar, M. E. (2020). Real-Time Hand Gesture Recognition: A Long Short-Term Memory Approach with Electromyography. Advances in Intelligent Systems and Computing, 1078, 155–167. https://doi.org/10.1007/978-3-030-33614-1_11
  16. Nogales, R., & Benalcázar, M. E. (2020). A Survey on Hand Gesture Recognition Using Machine Learning and Infrared Information. Communications in Computer and Information Science, 1194 CCIS, 297–311. https://doi.org/10.1007/978-3-030-42520-3_24
  17. Chung, E. A., & Benalcázar, M. E. (2019). Real-time hand gesture recognition model using deep learning techniques and EMG signals. European Signal Processing Conference, 2019-September. https://doi.org/10.23919/EUSIPCO.2019.8903136
  18. Benalcázar, M. E. (2019). Machine learning for computer vision: A review of theory and algorithms. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2019(19), 608–618. https://www.scopus.com/inward/record.uri?eid=2-s2.085069165385&partnerID=40&md5=fe293a6084a2a75a4e738211ce4c7301
  19. Benalcázar, M. E., Anchundia, C. E., Zea, J. A., Zambrano, P., Jaramillo, A. G., & Segura, M. (2018). Real-time hand gesture recognition based on artificial feed-forward neural networks and EMG. European Signal Processing Conference, 2018-Septe, 1492–1496. https://doi.org/10.23919/EUSIPCO.2018.8553126
  20. Motoche, C., & Benalcázar, M. E. (2018). Real-time hand gesture recognition based on electromyographic signals and artificial neural networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11139 LNCS, 352–361. https://doi.org/10.1007/978-3-030-01418-6_35
  21. Benalcázar, M. E., Jaramillo, A. G., Zea, J. A., Paéz, A., & Andaluz, V. H. (2017). Hand gesture recognition using machine learning and the myo armband. 25th European Signal Processing Conference, EUSIPCO 2017, 2017-January, 1040–1044. https://doi.org/10.23919/EUSIPCO.2017.8081366
  22. Estrada Jiménez, L. A., Benalcázar, M. E., & Sotomayor, N. (2017). Gesture recognition and machine learning applied to sign language translation. IFMBE Proceedings, 60, 233–236. https://doi.org/10.1007/978-981-10-4086-3_59

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