Jorge García-González

Orcid: 0000-0001-8610-3462

According to our database1, Jorge García-González authored at least 22 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Bibliography

2024
Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size.
Neurocomputing, January, 2024

DyNeRFactor: Temporally consistent intrinsic scene decomposition for dynamic NeRFs.
Comput. Graph., 2024

2023
Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm.
Neural Comput. Appl., September, 2023

Automated labeling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks.
Pattern Recognit. Lett., March, 2023

Automated detection of vehicles with anomalous trajectories in traffic surveillance videos.
Integr. Comput. Aided Eng., 2023

Optimized instance segmentation by super-resolution and maximal clique generation.
Integr. Comput. Aided Eng., 2023

2022
Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks.
Proceedings of the Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, 2022

Anomalous Trajectory Detection for Automated Traffic Video Surveillance.
Proceedings of the Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, 2022

Enhanced Image Segmentation by a Novel Test Time Augmentation and Super-Resolution.
Proceedings of the Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, 2022

Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021
Bayesian and Neural Inference on LSTM-Based Object Recognition From Tactile and Kinesthetic Information.
IEEE Robotics Autom. Lett., 2021

Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks.
Appl. Soft Comput., 2021

Foreground Segmentation Improvement by Image Denoising Preprocessing Applied to Noisy Video Sequences.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

2020
Background subtraction by probabilistic modeling of patch features learned by deep autoencoders.
Integr. Comput. Aided Eng., 2020

The effect of downsampling-upsampling strategy on foreground detection algorithms.
Artif. Intell. Rev., 2020

Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models.
Proceedings of the IEEE International Conference on Image Processing, 2020

Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences.
Pattern Recognit. Lett., 2019

Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders.
Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

2018
Background Modeling for Video Sequences by Stacked Denoising Autoencoders.
Proceedings of the Advances in Artificial Intelligence, 2018


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