Publicaciones en las que colabora con Santiago López Tapia (15)

2023

  1. Deep Robust Image Restoration Using the Moore-Penrose Blur Inverse

    Proceedings - International Conference on Image Processing, ICIP

  2. Learning Moore-Penrose based residuals for robust non-blind image deconvolution

    Digital Signal Processing: A Review Journal, Vol. 142

2021

  1. Deep learning approaches to inverse problems in imaging: Past, present and future

    Digital Signal Processing: A Review Journal, Vol. 119

  2. Gated recurrent networks for video super resolution

    European Signal Processing Conference

2019

  1. A composite discriminator for generative adversarial network based video super-resolution

    European Signal Processing Conference

  2. Deep CNNs for Object Detection Using Passive Millimeter Sensors

    IEEE Transactions on Circuits and Systems for Video Technology, Vol. 29, Núm. 9, pp. 2580-2589

  3. Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging Problems

    Proceedings - International Conference on Image Processing, ICIP

  4. Gan-Based Video Super-Resolution with Direct Regularized Inversion of the Low-Resolution Formation Model

    Proceedings - International Conference on Image Processing, ICIP

  5. Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution

    IEEE Transactions on Image Processing, Vol. 28, Núm. 7, pp. 3312-3327

  6. Multiple-degradation video super-resolution with direct inversion of the low-resolution formation model

    European Signal Processing Conference

  7. Semantic prior based generative adversarial network for video super-resolution

    European Signal Processing Conference

  8. Spatially Adaptive Losses for Video Super-resolution with GANs

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

2018

  1. Using machine learning to detect and localize concealed objects in passive millimeter-wave images

    Engineering Applications of Artificial Intelligence, Vol. 67, pp. 81-90