LCC - Contribuciones a congresos científicos
Envíos recientes
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A FaaS approach for long-term monitoring in rehabilitation
The function as a service (FaaS) model, in which the costs are linked to the function time of use, is especially suitable in IoT or similar systems, where the information is collected periodically to consume less energy. ... -
Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks
Pneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer- Aided Diagnosis (CAD) system for ... -
Stenosis detection in coronary angiography images using deep learning models
Luque-Baena, Rafael Marcos
; Romero Granados, Irene; Jiménez-Partinen, Ariadna; Palomo, Esteban José (2022)
The emergence of deep learning has caused its massive application to different fields in industry and research, among which is the clinical field, especially in those where the data is structured in the form of images ... -
Combining OCL and Natural Language: a Call for a Community Effort
Cabot, Jordi; Delgado, David; Burgueño-Caballero, Lola (ACM, 2022-10)
The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation ... -
Dataciones absolutas de yacimientos protohistóricos de la bahía de Málaga en el contexto de la primera presencia fenicia en el sur de la Península Ibérica
(XCIEFP 2022. X Congreso Internacional de Estudios Fenicios y Púnicos, 2022)En el presente artículo pretendemos aportar un nuevo conjunto de dataciones para la primera presencia fenicia en la bahía de Málaga. Así, se aportarán dataciones complementarias a las existentes en yacimientos fenicios y ... -
Moving object detection in noisy video sequences using deep convolutional disentangled representations.
García-González, Jorge; Luque-Baena, Rafael Marcos; Ortiz-de-Lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (2022)
Noise robustness is crucial when approaching a moving de- tection problem since image noise is easily mistaken for movement. In order to deal with the noise, deep denoising autoencoders are commonly proposed to be applied ... -
AndroCIES: Automatización de la certificación de seguridad para aplicaciones Android
Ruiz, Manuel; Rios-del-Pozo, Ruben; Roman-Castro, Rodrigo; Muñoz, Antonio; Martínez, Juan Manuel; Wallace, Jorge[et al.] (2022)
El auge de las plataformas móviles está impulsando el desarrollo de un gran número de aplicaciones, muchas de las cuales salen al mercado sin las convenientes comprobaciones de seguridad. Recientemente, Google está apostando ... -
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 ... -
Reconstruction of Gene Regulatory Networks with Multi-objective Particle Swarm Optimisers
Hurtado-Requena, Sandro Jose; Garcia-Nieto, Jose Manuel; Navas-Delgado, Ismael; Nebro-Urbaneja, Antonio Jesus; Aldana-Montes, Jose Francisco (2022-07-05)
The computational reconstruction of Gene Regulatory Networks (GRNs) from gene expression data has been modelled as a complex optimisation problem, which enables the use of sophisticated search methods to address it. ... -
Ontology-Driven Approach for KPI Meta-modelling, Selection and Reasoning
Roldan-Garcia, Maria del Mar; Garcia-Nieto, Jose Manuel; Maté, Alejandro; Trujillo, Juan; Aldana-Montes, Jose Francisco (2022-09)
A key challenge in current Business Analytics (BA) is the selection of suitable indicators for business objectives. This requires the exploration of business data through data-driven approaches, while modelling business ... -
FIMED: Flexible management of biomedical data
Hurtado-Requena, Sandro Jose; Garcia-Nieto, Jose Manuel; Navas-Delgado, Ismael; Aldana-Montes, Jose Francisco (2022-09-05)
In the last decade, clinical trial management systems have become an essential support tool for data management and analysis in clinical research. However, these clinical tools have design limitations, since they are ... -
Secure Mobile Agents on Embedded Boards: a TPM based solution
(ACM - ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security August 2022 Article No.: 104 Pages 1–7 https://doi.org/10.1145/3538969.3544419ARES 2022, 2022-08-26)La seguridad puede considerarse uno de los aspectos esenciales de cualquier sistema informático actual. El panorama actual evoluciona constantemente y aparecen nuevos modelos informáticos al mismo tiempo que surgen diferentes ... -
Enhanced Perspective Generation by Consensus of NeX neural models
Pacheco dos Santos Lima Junior, Marcos Sergio; Fernández Rodríguez, José David; Ortiz-de-Lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel; Domínguez-Merino, Enrique (2022-07)
Neural rendering is a relatively new field of research that aims to produce high quality perspectives of a 3D scene from a reduced set of sample images. This is done with the help of deep artificial neural networks that ... -
A Service for Flexible Management and Analysis of Heterogeneous Clinical Data
Garcia-Nieto, Jose Manuel; Navas-Delgado, Ismael; Hurtado-Requena, Sandro Jose (Springer, 2022-06-08)
Este documento describe FIMED 2.0, un servicio para la gestión flexible y análisis de datos clínicos heterogéneos. Esta herramienta de software permite la gestión flexible de datos clínicos de múltiples ensayos, lo que ... -
On the Use of Explainable Artificial Intelligence for the Differential Diagnosis of Pigmented Skin Lesions
Nematzadeh, Hossein; Navas-Delgado, Ismael; Berciano-Guerrero, Miguel Angel; Garcia-Nieto, Jose Manuel; Hurtado-Requena, Sandro Jose; Garcia-Nieto, Jose Manuel; Nematzadeh, Hossein[et al.] (Springer, 2022-06-08)
En los últimos años, la Inteligencia Artificial Explicable (XAI) ha atraído la atención en la analítica de datos, ya que muestra un gran potencial en la interpretación de los resultados de complejos modelos de aprendizaje ... -
Feature density as an uncertainty estimator method in the binary classification mammography images task for a supervised deep learning model
Hernández Vasquez, Marco A; Fuentes Fino, Ricardo Javier; Calderón-Ramírez, Saúl; Domínguez-Merino, Enrique; López-Rubio, Ezequiel; Molina-Cabello, Miguel Angel[et al.] (2022)
Labeled medical datasets may include a limited number of observations for each class, while unlabeled datasets may include observations from patients with pathologies other than those observed in the labeled dataset. This ... -
Encoding generative adversarial networks for defense against image classification attacks
Rodríguez Rodríguez, José Antonio; Pérez Bravo, José María; García González, Jorge; Molina-Cabello, Miguel Angel; Thurnhofer-Hemsi, Karl; López-Rubio, Ezequiel[et al.] (2022)
Image classification has undergone a revolution in recent years due to the high performance of new deep learning models. However, severe security issues may impact the performance of these systems. In particular, adversarial ... -
A novel continual learning approach for competitive neural networks
Fernández Rodríguez, José David; Maza Quiroga, Rosa María; Palomo-Ferrer, Esteban Jose; Ortiz-de-Lazcano-Lobato, Juan Miguel; López-Rubio, Ezequiel (2022)
Continual learning tries to address the stability-plasticity dilemma to avoid catastrophic forgetting when dealing with non-stationary distributions. Prior works focused on supervised or reinforcement learning, but few ... -
Analysis of functional connectome pipelines for the diagnosis of autism spectrum disorders
Maza Quiroga, Rosa María; Lopez-Rodriguez, Domingo; Thurnhofer-Hemsi, Karl; Luque-Baena, Rafael Marcos; Jiménez Valverde, Clara; López-Rubio, Ezequiel[et al.] (2022-05)
This paper explores the effect of using different pipelines to compute connectomes (matrices representing brain connections) and use them to train machine learning models with the goal of diagnosing Autism Spectrum ... -
Anomalous trajectory detection for automated traffic video surveillance
Fernández Rodríguez, Jose David; García-González, Jorge; Benitez-Rochel, Rafaela; Molina-Cabello, Miguel Angel; López-Rubio, Ezequiel; García-González, Jorge[et al.] (2022)
Vehicle trajectories extracted from traffic video sequences can be helpful for many purposes. In particular, the analysis of detected anomalous trajectories may enhance drivers’ safety. This work proposes a methodology to ...