Jorge García-González

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Video Sequences

Foreground Detection

Probabilistic Modeling

Background Modeling

Top Venues

Integr. Comput. Aided Eng.

Pattern Recognit. Lett.

Publications

Mario Alfonso-Arsuaga, Jorge García-González, Andrea Castiella-Aguirrezabala, Miguel Andrés Alonso, Elena Garces
DyNeRFactor: Temporally consistent intrinsic scene decomposition for dynamic NeRFs. Comput. Graph. 122 (2024)
Iván García Aguilar, Jorge García-González, Daniel Medina, Rafael Marcos Luque Baena, Enrique Domínguez, Ezequiel López-Rubio
Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size. Neurocomputing 567 (2024)
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio
Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm. Neural Comput. Appl. 35 (26) (2023)
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio
Automated labeling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks. Pattern Recognit. Lett. 167 (2023)
Iván García Aguilar, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio, Enrique Domínguez
Optimized instance segmentation by super-resolution and maximal clique generation. Integr. Comput. Aided Eng. 30 (3) (2023)
Jose David Fernández Rodriguez, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
Automated detection of vehicles with anomalous trajectories in traffic surveillance videos. Integr. Comput. Aided Eng. 30 (3) (2023)
Francisco Pastor, Jorge García-González, Juan M. Gandarias, Daniel Medina, Pau Closas, Alfonso J. García-Cerezo, Jesús M. Gómez de Gabriel
Bayesian and Neural Inference on LSTM-based Object Recognition from Tactile and Kinesthetic Information. CoRR (2023)
José M. Pérez-Bravo, José A. Rodríguez-Rodríguez, Jorge García-González, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks. IWINAC (1) (2022)
Jorge García-González, Iván García Aguilar, Daniel Medina, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Enrique Domínguez
Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks. SOCO (2022)
Iván García Aguilar, Jorge García-González, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Enrique Domínguez Merino
Enhanced Image Segmentation by a Novel Test Time Augmentation and Super-Resolution. IWINAC (1) (2022)
Jose D. Fernández, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Anomalous Trajectory Detection for Automated Traffic Video Surveillance. IWINAC (1) (2022)
Jorge García-González, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations. ICIP (2022)
Francisco Pastor, Jorge García-González, Juan M. Gandarias, Daniel Medina, Pau Closas, Alfonso J. García-Cerezo, Jesús M. Gómez de Gabriel
Bayesian and Neural Inference on LSTM-Based Object Recognition From Tactile and Kinesthetic Information. IEEE Robotics Autom. Lett. 6 (1) (2021)
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks. Appl. Soft Comput. 113 (Part) (2021)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
Background subtraction by probabilistic modeling of patch features learned by deep autoencoders. Integr. Comput. Aided Eng. 27 (3) (2020)
Miguel A. Molina-Cabello, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio
The effect of downsampling-upsampling strategy on foreground detection algorithms. Artif. Intell. Rev. 53 (7) (2020)
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models. ICIP (2020)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks. ECAI (2020)
Miguel A. Molina-Cabello, Jorge García-González, Rafael Marcos Luque Baena, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation. ICPR (2020)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio
Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders. IWINAC (2) (2019)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences. Pattern Recognit. Lett. 125 (2019)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Background Modeling for Video Sequences by Stacked Denoising Autoencoders. CAEPIA (2018)