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    المساهمون: Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària, Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny, Universitat Politècnica de València. Instituto de Seguridad Industrial, Radiofísica y Medioambiental - Institut de Seguretat Industrial, Radiofísica i Mediambiental, Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada

    Relation: IN-RED 2020: VI Congreso de Innovación Educativa y Docencia en Red; Julio 16-17, 2020; Valencia, España; http://ocs.editorial.upv.es/index.php/INRED/INRED2020/paper/view/11956; urn:isbn:978-84-9048-833-1; urn:issn:2603-5863; http://hdl.handle.net/10251/165446

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    Book

    المساهمون: Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials, Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny, Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials

    Relation: IN-RED 2020: VI Congreso de Innovación Educativa y Docencia en Red; Julio 16-17, 2020; Valencia, España; http://ocs.editorial.upv.es/index.php/INRED/INRED2020/paper/view/11998; urn:isbn:978-84-9048-833-1; urn:issn:2603-5863; http://hdl.handle.net/10251/166277

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    المصدر: Visión electrónica; Vol. 15 No. 1 (2021); 7-16 ; Visión electrónica; Vol. 15 Núm. 1 (2021); 7-16 ; 2248-4728 ; 1909-9746

    وصف الملف: application/pdf

    Relation: https://revistas.udistrital.edu.co/index.php/visele/article/view/17425/18664; H. Y. Vivian-Ip, A. Abrishami, P. W. H. Peng, J. Wong, F. Chung, “Predictors of Postoperative Pain and Analgesic Consumption: A Qualitative Systematic review”, Anesthesiology, vol. 111, no. 3, pp. 657–677, 2009. https://doi.org/10.1097/ALN.0b013e3181aae87a [2] O. L. Elvir-Lazo, P. F. White, “Postoperative pain management after ambulatory surgery: role of multimodal analgesia”, Anesthesiology Clinics, vol. 28, no. 2, pp. 217–224, 2010. https://doi.org/10.1016/j.anclin.2010.02.011 [3] American Academy of Pain Medicine, “Get the facts on pain”. [Online]. Available at http://www.painmed.org/patientcenter/facts-on-pain/ [4] P. J. Mathew, J. L. Mathew, “Assessment and management of pain in infants”, Postgraduate Medical Journal, vol. 79, no. 934, pp. 438–43, 2003. http://dx.doi.org/10.1136/pmj.79.934.438 [5] M. Clarett, “Escalas de evaluación de dolor y protocolo de analgesia en terapia intensiva”, Clínica y Maternidad Suizo Argentina Instituto Argentino de Diagnóstico y Tratamiento, Buenos Aires, Argentina, 2012. [6] L. J. Duhn, J. M. Medves, “A systematic integrative review of infant pain assessment tools”, Advance in Neonatal Care, vol. 4, no. 3, pp. 126–140, 2004. 10.1016/j.adnc.2004.04.005 [7] R. Slater, A. Cantarella, L. Franck, J. Meek, M. Fitzgerald, “How Well Do Clinical Pain Assessment Tools Reflect Pain in Infants?” PLoS Medicine, vol. 5, no. 6, p. 129, 2008. https://doi.org/10.1371/journal.pmed.0050129 [8] N. C. de Knegt. et al., “Behavioral Pain Indicators in People With Intellectual Disabilities: A Systematic Review”, The Journal of Pain, vol. 14, no. 9, pp. 885–896, 2013. https://doi.org/10.1016/j.jpain.2013.04.016 [9] G. Zamzmi, “An approach for automated multimodal analysis of infants’ pain”, 2016 23rd International Conference on Pattern Recognition (ICPR), pp. 4148–4153, 2016. [10] V. Guruswamy, “Assessment of pain in nonverbal children”, Association of Paediatric Anaesthetists of Great Britain and Ireland, no. 41, p. 33, 2014. [11] Registered Nurses’ Association of Ontario, “Assessment and management of pain”, vol. 3. Toronto, Canada, 2013. [12] R. Srouji, S. Ratnapalan, S. Schneeweiss, “Pain in Children: Assessment and Nonpharmacological Management”, International Journal of Pediatrics, 2010. https://doi.org/10.1155/2010/474838 [13] K. Brand, A. Al-Rais, “Pain assessment in children”, Anaesthesia and Intensive Care Medicine, vol. 20, no. 6, pp. 314–317, 2019. https://doi.org/10.1016/j.mpaic.2019.03.003 [14] D. Freund, B. N. Bolick, “Assessing a Child’s Pain”, AJN, American Journal of Nursing, vol. 119, no. 5, pp. 34–41, 2019. 10.1097/01.NAJ.0000557888.65961.c6 [15] M. Pérez, G. A. Cavanzo Nisso F. Villavisán Buitrago, “Sistema embebido de detección de movimiento mediante visión artificial ", Visión Electrónica, vol. 12, no. 1, pp. 97-101, 2018. https://doi.org/10.14483/22484728.15087 [16] J. F. Pantoja Benavides, F. N. Giraldo Ramos, Y. S. Rubio Valderrama, V. M. Rojas Lara, “Segmentación de imágenes utilizando campos aleatorios de Markov", Visión Electrónica, vol. 4, no. 2, pp. 5-16, 2010. https://doi.org/10.14483/22484728.432 [17] J. Forero C., C. Bohórquez, V. H. Ruiz, “Medición automatizada de piezas torneadas usando visión artificial", Visión Electrónica, vol. 7, no. 2, pp. 36-44, 2013. https://doi.org/10.14483/22484728.5507 [18] S. Brahnam, C.-F. Chuang, R. S. Sexton, F. Y. Shih, “Machine assessment of neonatal facial expressions of acute pain”, Decision Support System, vol. 43, no. 4, pp. 1242–1254, 2007. https://doi.org/10.1016/j.dss.2006.02.004 [19] A. Beltramini, K. Milojevic, D. Pateron, “Pain Assessment in Newborns, Infants, and Children”, Pediatric. Annals, vol. 46, no. 10, pp. 387–395, 2017. https://doi.org/10.3928/19382359-20170921-03 [20] X. Cong, J. M. McGrath, R. M. Cusson, D. Zhang, “Pain Assessment and Measurement in Neonates: An Ipdated Review”, Advances in Neonatal Care, vol. 13, no. 6, pp. 379–395, 2013. 10.1097/ANC.0b013e3182a41452 [21] C. L. von Baeyer L. J. Spagrud, “Systematic review of observational (behavioral) measures of pain for children and adolescents aged 3 to 18 years”, Pain, vol. 127, no. 1–2, pp. 140–150, 2007. https://doi.org/10.1016/j.pain.2006.08.014 [22] J. Zieliński, M. Morawska-Kochman, T. Zatoński, “Pain assessment and management in children in the postoperative period: A review of the most commonly used postoperative pain assessment tools, new diagnostic methods and the latest guidelines for postoperative pain therapy in children”, Advances in Clinical and Experimental Medicine, vol. 29, no. 3, pp. 365–374, 2020. 10.17219/acem/112600 [23] C. Greco, C. Berde, “Pain Management in Children”, Gregory’s Pediatric Anesthesia, Wiley, pp. 929–954, 2020. https://doi.org/10.1002/9781119371533.ch37 [24] G. Zamzmi, R. Kasturi, D. Goldgof, R. Zhi, T. Ashmeade, Y. Sun, “A Review of Automated Pain Assessment in Infants: Features, Classification Tasks, and Databases”, IEEE Reviews in Biomedical. Engineering, vol. 11, pp. 77–96, 2017. 10.1109/RBME.2017.2777907 [25] T. Voepel-Lewis, J. Zanotti, J. A. Dammeyer, S. Merkel, “Reliability and Validity of the Face, Legs, Activity, Cry, Consolability Behavioral Tool in Assessing Acute Pain in Critically Ill Patients”, American Journal of Critical Care, vol. 19, no. 1, pp. 55–61, 2010. https://doi.org/10.4037/ajcc2010624 [26] G. Guillen, “Digital Image Processing with Python and OpenCV”, Sensor Projects with Raspberry Pi, pp. 97–140, 2019. https://doi.org/10.1007/978-1-4842-5299-4_5 [27] R. Momtahina, M. Hossain, “Image Capturing and Automatic Face Recognition”, Dhaka, Bangladesh, 2019. [28] O. Subea, G. Suciu, “Facial Analysis Method for Pain Detection”, International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, pp. 167–180, 2019. https://doi.org/10.1007/978-3-030-23976-3_17 [29] D. E. King, “Dlib-ml: A Machine Learning Toolkit”, The Journal of Machine Learning Research, vol. 10, pp. 1755–1758, 2009. 10.1145/1577069.1755843 [30] K. He, X. Zhang, S. Ren, J. Sun, “Deep Residual Learning for Image Recognition”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [31] O. M. Parkhi, A. Vedaldi, A. Zisserman, “Deep face recognition”, Proceedings of the British Machine Vision Conference (BMVC), vol. 1, no. 3, p. 6, 2015. https://dx.doi.org/10.5244/C.29.41 [32] S. J. Pan, Q. Yang, “A Survey on Transfer Learning”, IEEE Transactions on knowledge and data engineering, vol. 22, no. 10, pp. 1345-1359, 2010. 10.1109/TKDE.2009.191 [33] F. Zhuang, “A Comprehensive Survey on Transfer Learning”, Proceedings of the IEEE, vol. 109, no. 1, pp. 1-34, 2019. 10.1109/JPROC.2020.3004555 [34] H.-W. Ng, V. D. Nguyen, V. Vonikakis, S. Winkler, “Deep Learning for Emotion Recognition on Small Datasets using Transfer Learning”, Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (ICMI ’15), pp. 443–449, 2015. https://doi.org/10.1145/2818346.2830593 [35] W. Ding, “Audio and face video emotion recognition in the wild using deep neural networks and small datasets”, Proceedings of the 18th ACM International Conference on Multimodal Interaction (ICMI ’1), pp. 506–513, 2016. https://doi.org/10.1145/2993148.2997637 [36] K. Zhang, L. Tan, Z. Li, Y. Qiao, “Gender and smile classification using deep convolutional neural networks”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [37] V. Campos, A. Salvador, B. Jou, X. Giró-i-Nieto, B. Jou, “Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction”, Proceedings of the 1st International Workshop on Affect & Sentiment in Multimedia (ASM '15), pp. 57-62, 2015. https://doi.org/10.1145/2813524.2813530 [38] H. Ding, S. K. Zhou, R. Chellappa, “FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition”, 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), pp. 118–126, 2017. 10.1109/FG.2017.23 [39] F. Wang, “Regularizing face verification nets for pain intensity regression”, in 2017 IEEE International Conference on Image Processing (ICIP), pp. 1087–1091, 2017. 10.1109/ICIP.2017.8296449 [40] M. S. Hossain, G. Muhammad, “Emotion recognition using deep learning approach from audio–visual emotional big data”, Information Fusion, vol. 49, pp. 69–78, 2019. https://doi.org/10.1016/j.inffus.2018.09.008; https://revistas.udistrital.edu.co/index.php/visele/article/view/17425

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    Academic Journal

    المؤلفون: Chinchay Puma, Cecilia

    المساهمون: Linares Guevara, Giancarlo

    المصدر: Universidad Católica Sedes Sapientiae ; Repositorio Institucional - UCSS

    وصف الملف: application/pdf

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    Academic Journal

    المؤلفون: Scarpa, Stefano

    المصدر: Formazione & insegnamento; Vol. 19 No. 3 (2021): Permanent Education from Early Childhood to Late Life; 340-351 ; Formazione & insegnamento; Vol. 19 Núm. 3 (2021): Educazione Permanente a partire dalle prime età della vita, per tutta la vita; 340-351 ; Formazione & insegnamento; V. 19 N. 3 (2021): Educazione Permanente a partire dalle prime età della vita, per tutta la vita; 340-351 ; 2279-7505 ; 1973-4778

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