Jorge García-González

25 papers A 1B 3Journal 13Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
Neuralux: Improving the decomposition of single-illumination multiview outdoor scenes.
Comput. Graph.
Mario Alfonso-Arsuaga, Andrea Castiella-Aguirrezabala, Jorge García-González, Jesús Bonilla, Jorge López-Moreno
2024 J jnl
Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size.
Neurocomputing
Iván García Aguilar, Jorge García-González, Daniel Medina, Rafael Marcos Luque Baena, Enrique Domínguez, Ezequiel López-Rubio
2024 J jnl
DyNeRFactor: Temporally consistent intrinsic scene decomposition for dynamic NeRFs.
Comput. Graph.
Mario Alfonso-Arsuaga, Jorge García-González, Andrea Castiella-Aguirrezabala, Miguel Andrés Alonso, Elena Garces
2024 — conf
Novel Positional Encoding Methods for Neural Rendering.
SOCO (2)
Daniel Molina-Pinel, Jorge García-González, Enrique Domínguez, Ezequiel López-Rubio
2023 J jnl
Automated detection of vehicles with anomalous trajectories in traffic surveillance videos.
Integr. Comput. Aided Eng.
Jose David Fernández Rodriguez, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
2023 J jnl
Automated labeling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks.
Pattern Recognit. Lett.
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio
2023 J jnl
Bayesian and Neural Inference on LSTM-based Object Recognition from Tactile and Kinesthetic Information.
CoRR
Francisco Pastor, Jorge García-González, Juan M. Gandarias, Daniel Medina, Pau Closas, Alfonso J. García-Cerezo, Jesús M. Gómez de Gabriel
2023 J jnl
Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm.
Neural Comput. Appl.
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio
2023 J jnl
Optimized instance segmentation by super-resolution and maximal clique generation.
Integr. Comput. Aided Eng.
Iván García Aguilar, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio, Enrique Domínguez
2022 — conf
Anomalous Trajectory Detection for Automated Traffic Video Surveillance.
IWINAC (1)
Jose D. Fernández, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2022 — conf
Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks.
IWINAC (1)
José M. Pérez-Bravo, José A. Rodríguez-Rodríguez, Jorge García-González, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
2022 — conf
Enhanced Image Segmentation by a Novel Test Time Augmentation and Super-Resolution.
IWINAC (1)
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Enrique Domínguez Merino
2022 B conf
Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations.
ICIP
Jorge García-González, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
2022 — conf
Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks.
SOCO
Jorge García-González, Iván García Aguilar, Daniel Medina, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Enrique Domínguez
2021 J jnl
Bayesian and Neural Inference on LSTM-Based Object Recognition From Tactile and Kinesthetic Information.
IEEE Robotics Autom. Lett.
Francisco Pastor, Jorge García-González, Juan M. Gandarias, Daniel Medina, Pau Closas, Alfonso J. García-Cerezo, Jesús M. Gómez de Gabriel
2021 — conf
Foreground Segmentation Improvement by Image Denoising Preprocessing Applied to Noisy Video Sequences.
SOCO
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael Marcos Luque Baena, Ezequiel López-Rubio
2021 J jnl
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks.
Appl. Soft Comput.
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
2020 B conf
Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation.
ICPR
Miguel A. Molina-Cabello, Jorge García-González, Rafael Marcos Luque Baena, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
2020 J jnl
Background subtraction by probabilistic modeling of patch features learned by deep autoencoders.
Integr. Comput. Aided Eng.
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
2020 B conf
Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models.
ICIP
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
2020 A conf
Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks.
ECAI
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
2020 J jnl
The effect of downsampling-upsampling strategy on foreground detection algorithms.
Artif. Intell. Rev.
Miguel A. Molina-Cabello, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio
2019 — conf
Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders.
IWINAC (2)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
2019 J jnl
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences.
Pattern Recognit. Lett.
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2018 — conf
Background Modeling for Video Sequences by Stacked Denoising Autoencoders.
CAEPIA
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio