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dc.contributor.authorBallesteros, Dora Maria
dc.date.accessioned2020-01-08T19:11:42Z
dc.date.available2020-01-08T19:11:42Z
dc.date.issued2019-11-25
dc.identifierhttp://revistas.unimilitar.edu.co/index.php/rcin/article/view/4354
dc.identifier10.18359/rcin.4354
dc.identifier.urihttp://hdl.handle.net/10654/33467
dc.descriptionArtificial intelligence (AI) is an interdisciplinary subject in science and engineering that makes it possible for machines to learn from data. Artificial Intelligence applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1, 3], support vector machine applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7] and big data analytics for natural disasters [8].eng
dc.descriptionArtificial intelligence (AI) is an interdisciplinary subject in science and engineering that makes it possible for machines to learn from data. Artificial Intelligence applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1, 3], support vector machine applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7] and big data analytics for natural disasters [8].spa
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherUniversidad Militar Nueva Granadaspa
dc.rightsDerechos de autor 2019 Ciencia e Ingeniería Neogranadinaspa
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0spa
dc.sourceCiencia e Ingenieria Neogranadina; Vol 30 No 1 (2020)eng
dc.sourceCiencia e Ingeniería Neogranadina; Vol. 30 Núm. 1 (2020)spa
dc.sourceCiencia e Ingeniería Neogranadina; v. 30 n. 1 (2020)por
dc.source1909-7735
dc.source0124-8170
dc.titleSpecial Issue in Artificial Intelligenceeng
dc.titleSpecial Issue in Artificial Intelligencespa
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typetextoeng
dc.relation.referenceshttp://revistas.unimilitar.edu.co/index.php/rcin/article/view/4354/3396
dc.relation.references/*ref*/Perdomo Charry, O. J., & González Osorio, F. A. (2019). A Systematic Review of Deep Learning Methods Applied to Ocular Images. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.4242 [2] Martin, L. D., Medina, J., & Upegui, E. (2019). Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia). Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.3842 [3] Castillo, J. A., Granados, Y. C., & Fajardo Ariza, C. A. (2019). Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.4156 [4] Muñoz Peña, K., & Bacca Cortes, B. (2019). GUI3DXBot: An Interactive Software Tool for a Tour-Guide Mobile Robot. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.3644 [5] Leal Piedrahita, E. A. (2019). Hierarchical Clustering for Anomalous Traffic Conditions Detection in Power Substations. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.4236 [6] Florez Zuluaga, J. A., Patino Carrasco, E., Ortega Pabon, J. D., Gallego Leon, K., & Quintero Montoya, O. L. (2019). A Data Fusion System for Simulation of Critical Scenarios and Decision-Making. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.4131 [7] González, E., Villamizar Luna, W. D., & Fajardo Ariza, C. A. (2019). A Hardware Accelerator for the Inference of a Convolutional Neural network. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.4194 [8] Martínez Quezada, D. O., Sierra Robinson, R., Martínez Cano, J. G., & Lamos Díaz, H. (2019). Stakeholders Identification in a Disaster Through Twitter: Study Case SINABUNG 2018. Ciencia E Ingenieria Neogranadina, 30(1). https://doi.org/10.18359/rcin.3938
dc.subject.proposalDeep learningeng
dc.subject.proposalSupport Vector Machineseng
dc.subject.proposalClusteringeng
dc.subject.proposalExpert systemseng
dc.subject.proposalBig data analyticseng


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