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Publicaciones
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- Vásconez, J., Barona López, L., Valdiviezo Caraguay, Á., & Benalcázar, M. (2023). A comparison of EMG-based hand gesture recognition systems based on supervised and reinforcement learning. Engineering Applications of Artificial Intelligence, 123, 106327.
- Mantilla, C., Barona, L., Valdivieso, A., & Benalcázar, M. (2023). Arquitectura de Medición del Impacto de Ataques DoS en QoS/QoE de Servicios Multimedia en Redes SDN. Revista Ibérica de Sistemas e Tecnologias de Informação, 29-43. Obtenido de https://bvirtual.epn.edu.ec/scholarly-journals/arquitectura-de-medición-del-impacto-ataques-dos/docview/2828430682/se-2
- Díaz, D., Benalcázar, M., Barona, L., & Valdivieso, Á. (s.f.). Development of a Hand Gesture Recognition Model Capable of Online Readjustment Using EMGs and Double Deep-Q Networks. In: Rocha, Á., Ferrás, C., Ibarra, W. (eds) Information Technology and Systems. ICITS 2023. Lecture Notes in Networks and Systems, 691, 361-371. doi: https://doi.org/10.1007/978-3-031-33258-6_34
- Nogales, R., & Benalcázar , M. (2023). Hand Gesture Recognition Using Automatic Feature Extraction and Deep Learning Algorithms with Memory. Big Data and Cognitive Computing, 7(2), 102. doi: https://doi.org/10.3390/bdcc7020102
- Vásconez, J., Barona López, L., Valdivieso Caraguay, Á., & Benalcázar, M. (2022). Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks. Sensors, 22(24), 9613. doi: https://doi.org/10.3390/s22249613
- Martínez, R., Nogales, R., Benalcázar, M., & Naranjo, H. (s.f.). Home Automation System for People with Limited Upper Limb Capabilities Using Artificial Intelligence. In: Garcia, M.V., Gordón-Gallegos, C. (eds) CSEI: International Conference on Computer Science, Electronics and Industrial Engineering (CSEI). CSEI 2022. Lecture Notes in Networks and Systems. 678. Springer,Cham. doi: https://doi.org/10.1007/978-3-031-30592-4_16
- Valdivieso Caraguay, Á., Vásconez, J., Barona López, L., & Benalcázar, M. (2023). Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks. Sensors 2023, 23(8), 3905. doi: https://doi.org/10.3390/s23083905
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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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