Listar por tema "Object detection"
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 ... -
Automated detection of vehicles with anomalous trajectories in traffic surveillance videos.
Fernández-Rodríguez, Jose David; García-González, Jorge; Benítez-Rochel, Rafaela; Molina-Cabello, Miguel Ángel; Ramos-Jiménez, Gonzalo Pascual; López-Rubio, Ezequiel[et al.] (IOS Press, 2023-05-10)
Video feeds from traffic cameras can be useful for many purposes, the most critical of which are related to monitoring road safety. Vehicle trajectory is a key element in dangerous behavior and traffic accidents. In this ... -
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 ... -
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 ... -
Hierarchical matching using submap isomorphism
(Servicio de Publicaciones y Divulgación Científica, 2015)This Ph.D. Thesis presents a novel part-based approach for automatic object detection in real scenes. For that purpose, the scene is represented using a novel perceptual segmentation approach, also presented in this thesis, ... -
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 ... -
Parallel proccessing applied to object detection with a Jetson TX2 embedded system.
Benito-Picazo, Jesús; Fernández-Rodríguez, Jose David; Domínguez-Merino, Enrique; Palomo-Ferrer, Esteban José; López-Rubio, Ezequiel (2023)
Video streams from panoramic cameras represent a powerful tool for automated surveillance systems, but naïve implementations typically require very intensive computational loads for applying deep learning models for automated ... -
Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis
Chaves García, Antonio Jesús; Martín-Fernández, Cristian; Llopis-Torres, Luis Manuel; Díaz-Rodríguez, Manuel; Ruiz-Mata, Rocío; Gálvez-Montañez, Enrique de; Recio-Criado, María Marta; Trigo-Pérez, María del Mar; Picornell Rodríguez, Antonio[et al.] (Springer Nature, 2023-12-20)
Airborne pollen is produced by plants for their sexual reproduction and can have negative impacts on public health. The current monitoring systems are based on manual sampling processes which are tedious and time-consuming. ... -
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks
García-González, Jorge; Molina-Cabello, Miguel Ángel; Luque-Baena, Rafael Marcos; Ortiz-de-Lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (ELSEVIER, 2021-12)
Air quality and reduction of emissions in the transport sector are determinant factors in achieving a sustainable global climate. The monitoring of emissions in traffic routes can help to improve route planning and to ... -
Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences.
Fernández-Rodríguez, Jose David; Carmona-Martínez, Pablo; Benítez-Rochel, Rafaela; Molina-Cabello, Miguel Ángel; López-Rubio, Ezequiel (Springer, 2024)
As traffic cameras become prevalent, and a considerable amount of traffic videos are stored for various purposes, new possibilities and challenges open in the automatic analysis of traffic scenes. Advances in deep ... -
ViMantic, a distributed robotic architecture for semantic mapping in indoor environments
Fernández-Chaves, David; Ruiz-Sarmiento, José Raúl; Petkov, Nicolai; González-Jiménez, Javier Poncela; González-Jiménez, Javier Poncela (ELSEVIER, 2021-11-28)
Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. ...