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Ecuadorian traffic sign detection through color information and a convolutional neural network
Conference ObjectAbstract: This article develops an algorithm for the detection and recognition of regulatory and warning traffPalabras claves:COLOR, Deep learning, ECUADOR, Regulatory sign, traffic accidents, Warning signAutores:Gallegos J., Gonzalo Patricio Espinel, José Luis Carrillo-Medina, Marco Javier Flores-Calero, Marco V. Gualsaquí, Maria Jose Ayala, Patricio Espinel, Patricio VizcainoFuentes:googlescopusA Hybrid Evolutionary CNN-LSTM Model for Prognostics of C-MAPSS Aircraft Dataset
Conference ObjectAbstract: The fundamental concept of prognostics and health management (PHM) is to find an approach to evaluatPalabras claves:Aircraft engines, C-MAPSS, CNN, Deep learning, LSTM, Prognostics and Health ManagementAutores:Alex Davila-Frias, Buakum D., Grewell D., Khumprom P.Fuentes:googlescopusA Survey of Deep Learning Based NOMA: State of the Art, Key Aspects, Open Challenges and Future Trends
ReviewAbstract: Non-Orthogonal Multiple Access (NOMA) has become a promising evolution with the emergence of fifth-gPalabras claves:Channel State Information (CSI), Deep learning, massive connectivity, NOMA, Resource allocation, Spectral efficiency, Successive Interference Cancellation (SIC)Autores:Elfikky A., José Varela-Aldás, Li Y., Mohsan S.A.H., Mostafa S.M., Shvetsov A.V., Yanlong LiFuentes:googlescopusA Systematic Literature Review of Learning-Based Traffic Accident Prediction Models Based on Heterogeneous Sources
ReviewAbstract: Statistics affirm that almost half of deaths in traffic accidents were vulnerable road users, such aPalabras claves:Deep learning, heterogeneous sources, Machine Learning, Neural network, traffic accident pbkp_rediction, Traffic accident predictionAutores:Ángel Leonardo Valdivieso Caraguay, Myriam Hernández-Alvarez, Pablo MarcilloFuentes:googlescopusA deep learning approach for automatic recognition of seismo-volcanic events at the Cotopaxi volcano
ArticleAbstract: The research for developing an automatic recognition system of volcanic microearthquakes have been aPalabras claves:convolutional neural networks, Deep learning, Periodogram, Spectrogram, Volcanic microearthquakesAutores:Fernando Lara-Lara, JULIO CESAR LARCO BRAVO, Ricardo Carrera, Roman Lara-Cueva, RUBEN DARIO LEON VASQUEZ, Ruben LeónFuentes:googlescopusA novel methodology for optimal location of reactive compensation through deep neural networks
ArticleAbstract: The present investigation proposes a methodology for the optimal location of reactive compensation iPalabras claves:Deep learning, Electrical Power System, Multi-layer neural network, reactive compensationAutores:Jorge Paúl Muñoz Pilco, Luis Tipán , Manuel Dario Jaramillo MongeFuentes:googleorcidscopusA survey on deep learning for cybersecurity: Progress, challenges, and opportunities
OtherAbstract: As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult toPalabras claves:Artificial intelligence, Botnets, Cyber-threat, Cybersecurity, Deep learning, Encrypted traffic analysis, intrusion detection, Machine Learning, Spam filteringAutores:Mayra MacAs, WALTER MARCELO FUERTES DÍAZ, Wu C.Fuentes:googleorcidscopusA synthetic Data Generator for Smart Grids based on the Variational-Autoencoder Technique and Linked Data Paradigm
Conference ObjectAbstract: In a smart environment like the smart grids, it is necessary to have knowledge models that allow solPalabras claves:Deep learning, Linked data, Smart grid, Synthetic Data Generator, Variational autoencodersAutores:Dos Santos R., José Lisandro Aguilar Castro, R-Moreno M.D., Santos R.D.Fuentes:scopusTowards a low-cost embedded vehicle counting system based on deep-learning for traffic management applications
Conference ObjectAbstract: This paper explores the feasibility of using a low-cost embedded system for real-time vehicle detectPalabras claves:Centroid, Deep learning, Kalman filter, Neural computer stick (NCS2), Raspberry PI, tracking, Vehicle recognition, YOLOv4 tinyAutores:Daniel Riofrio, Diego S. Benitez, Josue Navarro, Noel Perez, Ricardo Flores MoyanoFuentes:scopusTransfer Learning in Breast Mammogram Abnormalities Classification with Mobilenet and Nasnet
Conference ObjectAbstract: Breast cancer has an important incidence in women mortality worldwide. Currently, mammography is conPalabras claves:Deep learning, digital mammogram, image pre-processing, Machine Learning, Transfer learningAutores:Lenin G. Falconi, María Perez, Wilbert G. AguilarFuentes:scopus