Listar por autor "García Aguilar, Iván"
Mostrando ítems 1-13 de 13
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Automate d lab eling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks
García Aguilar, Iván; García-González, Jorge; Luque-Baena, Rafael Marcos
; López-Rubio, Ezequiel (Elsevier, 2023)
The exponential increase in the use of technology in road management systems has led to real-time vi- sual information in thousands of locations on road networks. A previous step in preventing or detecting accidents involves ... -
Deep Learning Neural Networks to Improve Small Object Detection.
(UMA Editorial, 2024)This Ph.D. thesis is about enhancing small object detection and segmentation in road video sequences by integrating convolutional neural networks (CNNs) and super-resolution (SR) techniques. In response to the increasing ... -
Desarrollo de una API REST para la optimización de los tiempos de espera de las peticiones de renderizado de una aplicación web.
(2024)Actualmente, las tecnologías web constituyen la base de multitud de aplicaciones y servicios, siendo gran parte de estos de una gran escala y estando orientados a servir a un elevado número de clientes, ya sean usuarios ... -
Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size
García Aguilar, Iván; García-González, Jorge; Medina, Daniel; Luque-Baena, Rafael Marcos; Domínguez-Merino, Enrique; López-Rubio, Ezequiel[et al.] (Elsevier, 2023-11-17)
Autonomous driving requires information such as the velocity of other vehicles to prevent potential hazards. This work proposes a real-time deep learning-based framework to estimate vehicle speeds from image captures through ... -
Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference.
García Aguilar, Iván; Rostyslav, Zavoiko; Fernández-Rodríguez, Jose David; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (Springer, 2024)
Histopathology currently serves as the standard for breast cancer diagnosis, but its manual execution demands time and expertise from pathologists. Artificial intelligence, particularly in digital pathology, has made ... -
Estudio sobre la mejora en la detección de objetos pequeños mediante técnicas de procesamiento de imágenes y super-resolución.
(2022-12)Los drones son un tipo de vehículo aéreo no tripulado (UAV) los cuales en los últimos años se han convertido en una herramienta indispensable en multitud de tareas debido a su enorme utilidad, bajo coste y facilidad de ... -
Implementación de una librería de seguridad mediante el módulo de plataforma confiable sobre Sistemas de Agentes Móviles
(2020-11-24)El principal objetivo de este trabajo fin de grado, ha sido establecer e implantar un protocolo que permita la comunicación de forma segura, entre agentes móviles distribuidos a través de la red, haciendo uso de ... -
Improved detection of small objects in road network sequences using CNN and super resolution
The detection of small objects is one of the problems present in deep learning due to the context of the scene or the low number of pixels of the objects to be detected. According to these problems, current pre-trained ... -
Optimized instance segmentation by super-resolution and maximal clique generation.
García Aguilar, Iván; García-González, Jorge; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Domínguez-Merino, Enrique (IOS press, 2023-05-10)
The rise of surveillance systems has led to exponential growth in collected data, enabling several advances in Deep Learning to exploit them and automate tasks for autonomous systems. Vehicle detection is a crucial task ... -
Prediction of Optimal Locations for 5G Base Stations in Urban Environments Using Neural Networks and Satellite Image Analysis.
García Aguilar, Iván; Galeano-Brajones, Jesús; Luna-Valero, Francisco; Carmona Murillo, Javier; Fernández-Rodríguez, Jose David; Luque-Baena, Rafael Marcos[et al.] (Springer, 2024)
Deploying 5G networks in urban areas is crucial for meeting the increasing demand for high-speed, low-latency wireless communications. However, the complex topography and diverse building structures in urban environments ... -
Small-Scale Urban Object Anomaly Detection Using Convolutional Neural Networks with Probability Estimation.
García Aguilar, Iván; Luque-Baena, Rafael Marcos; Domínguez-Merino, Enrique; López-Rubio, Ezequiel (MDPI, 2023-08-15)
Anomaly detection in sequences is a complex problem in security and surveillance. With the exponential growth of surveillance cameras in urban roads, automating them to analyze the data and automatically identify anomalous ... -
Vehicle overtaking hazard detection over onboard cameras using deep convolutional networks
García-González, Jorge; García Aguilar, Iván; Medina, Daniel; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel; Domínguez, Enrique[et al.] (2022)
The development of artificial vision systems to support driving has been of great interest in recent years, especially after new learning models based on deep learning. In this work, a framework is proposed for detecting ...