Special Issue in Artificial Intelligence
Abstract
Artificial 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].
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Disciplines:
Artificial IntelligenceLanguages:
EnglishSupport agencies:
Universidad Militar Nueva GranadaRights:
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textoReferences
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
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
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
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
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
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
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
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
