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Rafael Molina 0001
Rafael Molina Soriano
Person information
- affiliation: University of Granada, Department of Computer Science and Artificial Intelligence, Spain
Other persons with the same name
- Rafael Molina 0002
— Institute of Physical Chemistry Rocasolano, Deparment of Crystallography and Structural Biology, Madrid, Spain
- Rafael Molina 0003 — Illinois Institute of Technology, Chicago, IL, USA
- Rafael Molina 0004 — Castilla La Mancha University, Spain
- Rafael Molina 0005
- Rafael Molina 0006 — Universidad Distrital Francisco José de Caldas, Bogotá, Colombia
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2020 – today
- 2024
- [j97]Francisco M. Castro-Macías
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection. Artif. Intell. 331: 104115 (2024) - [j96]Fernando Pérez-Bueno
Robust blind color deconvolution and blood detection on histological images using Bayesian K-SVD. Artif. Intell. Medicine 156: 102969 (2024) - [j95]Neel Kanwal
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images. Comput. Medical Imaging Graph. 112: 102321 (2024) - [j94]Miguel López-Pérez
Learning from crowds for automated histopathological image segmentation. Comput. Medical Imaging Graph. 112: 102327 (2024) - [j93]Miguel López-Pérez
The CrowdGleason dataset: Learning the Gleason grade from crowds and experts. Comput. Methods Programs Biomed. 257: 108472 (2024) - [j92]Shuowen Yang, Fernando Pérez-Bueno
BCD-net: Stain separation of histological images using deep variational Bayesian blind color deconvolution. Digit. Signal Process. 145: 104318 (2024) - [j91]Jose Pérez-Cano
An end-to-end approach to combine attention feature extraction and Gaussian Process models for deep multiple instance learning in CT hemorrhage detection. Expert Syst. Appl. 240: 122296 (2024) - [j90]Arne Schmidt
Focused active learning for histopathological image classification. Medical Image Anal. 95: 103162 (2024) - [j89]Pablo Morales-Álvarez
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images. Pattern Recognit. 146: 110057 (2024) - [j88]Xinyi Wu
Real-Time Lightweight Video Super-Resolution With RRED-Based Perceptual Constraint. IEEE Trans. Circuits Syst. Video Technol. 34(10): 10310-10325 (2024) - [j87]Arne Schmidt
Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10909-10922 (2024) - [c133]Francisco M. Castro-Macías
Blind Color Deconvolution and Classification of Histological Images Using the Hyperbolic Secant Prior. ISBI 2024: 1-5 - [i18]Xijun Wang, Santiago López-Tapia, Alice Lucas, Xinyi Wu, Rafael Molina, Aggelos K. Katsaggelos:
A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models. CoRR abs/2403.10589 (2024) - [i17]Francisco M. Castro-Macías
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection. CoRR abs/2403.14829 (2024) - [i16]Arne Schmidt, Pablo Morales-Álvarez, Lee A. D. Cooper, Lee A. Newberg, Andinet Enquobahrie, Aggelos K. Katsaggelos, Rafael Molina:
Focused Active Learning for Histopathological Image Classification. CoRR abs/2404.04663 (2024) - [i15]Francisco M. Castro-Macías, Pablo Morales-Álvarez, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos:
Sm: enhanced localization in Multiple Instance Learning for medical imaging classification. CoRR abs/2410.03276 (2024) - 2023
- [j86]Miguel López-Pérez
Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification. IEEE Access 11: 6922-6934 (2023) - [j85]Rocío del Amor
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset. Artif. Intell. Medicine 145: 102686 (2023) - [j84]Santiago López-Tapia, Javier Mateos
Learning Moore-Penrose based residuals for robust non-blind image deconvolution. Digit. Signal Process. 142: 104193 (2023) - [j83]Pablo Ruiz
Probabilistic fusion of crowds and experts for the search of gravitational waves. Knowl. Based Syst. 261: 110183 (2023) - [c132]Fernando Pérez-Bueno
A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H &E Histological Images. AIME 2023: 207-217 - [c131]Miguel López-Pérez
Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students. AIME 2023: 245-249 - [c130]Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina:
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation. ICCV 2023: 21040-21049 - [c129]Shuowen Yang, Fernando Pérez-Bueno
Deep Bayesian Blind Color Deconvolution of Histological Images. ICIP 2023: 710-714 - [c128]Santiago López-Tapia, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos:
Deep Robust Image Restoration Using the Moore-Penrose Blur Inverse. ICIP 2023: 775-779 - [c127]Yunan Wu, Francisco M. Castro-Macías
Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection. MICCAI (5) 2023: 327-337 - [d1]Fernando Pérez-Bueno
Practicas Jupyter para Extracción de Carácteristicas en Imágenes (Master DATCOM 21/22). Zenodo, 2023 - [i14]Fernando Pérez-Bueno
Leveraging a Probabilistic PCA Model to Understand the Multivariate Statistical Network Monitoring Framework for Network Security Anomaly Detection. CoRR abs/2302.01759 (2023) - [i13]Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina:
Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning. CoRR abs/2302.04061 (2023) - [i12]Yunan Wu, Francisco M. Castro-Macías, Pablo Morales-Álvarez, Rafael Molina, Aggelos K. Katsaggelos:
Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection. CoRR abs/2307.09457 (2023) - [i11]Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina:
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation. CoRR abs/2307.11397 (2023) - [i10]Pablo Morales-Álvarez, Arne Schmidt, José Miguel Hernández-Lobato, Rafael Molina:
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images. CoRR abs/2310.19359 (2023) - 2022
- [j82]Arne Schmidt
Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning. IEEE Access 10: 9763-9773 (2022) - [j81]Neel Kanwal
The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A Review. IEEE Access 10: 58821-58844 (2022) - [j80]Julio Silva-Rodríguez, Arne Schmidt
Proportion constrained weakly supervised histopathology image classification. Comput. Biol. Medicine 147: 105714 (2022) - [j79]Fernando Pérez-Bueno
Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification. Comput. Medical Imaging Graph. 97: 102048 (2022) - [j78]Miguel López-Pérez
Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection. Comput. Methods Programs Biomed. 219: 106783 (2022) - [j77]Pablo Morales-Álvarez
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO. IEEE Trans. Pattern Anal. Mach. Intell. 44(3): 1534-1551 (2022) - [j76]Fernando Pérez-Bueno
Leveraging a Probabilistic PCA Model to Understand the Multivariate Statistical Network Monitoring Framework for Network Security Anomaly Detection. IEEE/ACM Trans. Netw. 30(3): 1217-1229 (2022) - 2021
- [j75]Fernando Pérez-Bueno
Blind color deconvolution, normalization, and classification of histological images using general super Gaussian priors and Bayesian inference. Comput. Methods Programs Biomed. 211: 106453 (2021) - [j74]Santiago López-Tapia
Deep learning approaches to inverse problems in imaging: Past, present and future. Digit. Signal Process. 119: 103285 (2021) - [j73]Miguel López-Pérez
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes. IEEE Trans. Geosci. Remote. Sens. 59(5): 3875-3890 (2021) - [c126]Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández-Lobato:
Activation-level uncertainty in deep neural networks. ICLR 2021 - [c125]Yunan Wu, Arne Schmidt
Combining Attention-Based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection. MICCAI (2) 2021: 582-591 - [i9]Daniel Heestermans Svendsen, Pablo Morales-Alvarez, Ana Belen Ruescas, Rafael Molina, Gustau Camps-Valls:
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion. CoRR abs/2104.10638 (2021) - [i8]Julio Silva-Rodríguez, Adrián Colomer, María Á. Sales, Rafael Molina, Valery Naranjo:
Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection. CoRR abs/2105.10490 (2021) - 2020
- [j72]Julio Silva-Rodríguez
Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection. Comput. Methods Programs Biomed. 195: 105637 (2020) - [j71]Fernando Pérez-Bueno
A TV-based image processing framework for blind color deconvolution and classification of histological images. Digit. Signal Process. 101: 102727 (2020) - [j70]Santiago López-Tapia, Alice Lucas
A single video super-resolution GAN for multiple downsampling operators based on pseudo-inverse image formation models. Digit. Signal Process. 104: 102801 (2020) - [j69]Fernando Pérez-Bueno
Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors. Sensors 20(18): 5308 (2020) - [j68]Natalia Hidalgo-Gavira, Javier Mateos, Miguel Vega
Variational Bayesian Blind Color Deconvolution of Histopathological Images. IEEE Trans. Image Process. 29: 2026-2036 (2020) - [j67]Xu Zhou
Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy. IEEE Trans. Image Process. 29: 3227-3238 (2020) - [c124]Santiago López-Tapia, Alice Lucas, Rafael Molina
Gated Recurrent Networks for Video Super Resolution. EUSIPCO 2020: 700-704 - [c123]Fernando Pérez-Bueno
Fully Automatic Blind Color Deconvolution of Histological Images Using Super Gaussians. EUSIPCO 2020: 1254-1258 - [c122]Fernando Pérez-Bueno
Super Gaussian Priors for Blind Color Deconvolution of Histological Images. ICIP 2020: 3010-3014 - [i7]Daniel Heestermans Svendsen, Pablo Morales-Álvarez, Rafael Molina, Gustau Camps-Valls:
Deep Gaussian Processes for geophysical parameter retrieval. CoRR abs/2012.12099 (2020)
2010 – 2019
- 2019
- [j66]Ángel E. Esteban, Miguel López-Pérez
A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes. Comput. Methods Programs Biomed. 178: 303-317 (2019) - [j65]Juan G. Serra, Javier Mateos
Variational EM method for blur estimation using the spike-and-slab image prior. Digit. Signal Process. 88: 116-129 (2019) - [j64]Pablo Morales-Alvarez
Scalable and efficient learning from crowds with Gaussian processes. Inf. Fusion 52: 110-127 (2019) - [j63]Pablo Ruiz
Learning from crowds with variational Gaussian processes. Pattern Recognit. 88: 298-311 (2019) - [j62]Santiago López-Tapia
Deep CNNs for Object Detection Using Passive Millimeter Sensors. IEEE Trans. Circuits Syst. Video Technol. 29(9): 2580-2589 (2019) - [j61]Alice Lucas
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. IEEE Trans. Image Process. 28(7): 3312-3327 (2019) - [c121]Santiago Lopez Tapia, Alice Lucas
Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation Model. EUSIPCO 2019: 1-5 - [c120]Miguel Vega, Javier Mateos, Rafael Molina
Variational Bayes Color Deconvolution with a Total Variation Prior. EUSIPCO 2019: 1-5 - [c119]Xijun Wang, Alice Lucas, Santiago Lopez Tapia, Xinyi Wu, Rafael Molina
A Composite Discriminator for Generative Adversarial Network based Video Super-Resolution. EUSIPCO 2019: 1-5 - [c118]Xinyi Wu, Alice Lucas, Santiago López-Tapia, Xijun Wang, Yul Hee Kim, Rafael Molina
Semantic Prior Based Generative Adversarial Network for Video Super-Resolution. EUSIPCO 2019: 1-5 - [c117]Xijun Wang, Alice Lucas, Santiago Lopez Tapia, Xinyi Wu, Rafael Molina
Spatially Adaptive Losses for Video Super-resolution with GANs. ICASSP 2019: 1697-1701 - [c116]Santiago López-Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos
Gan-Based Video Super-Resolution With Direct Regularized Inversion of the Low-Resolution Formation Model. ICIP 2019: 2886-2890 - [c115]Alice Lucas
Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging Problems. ICIP 2019: 3591-3595 - [c114]Miguel López-Pérez
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor. IDEAL (1) 2019: 39-46 - [i6]Santiago López-Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos:
A Single Video Super-Resolution GAN for Multiple Downsampling Operators based on Pseudo-Inverse Image Formation Models. CoRR abs/1907.01399 (2019) - [i5]Pablo Morales-Alvarez, Pablo Ruiz, Scott Coughlin, Rafael Molina, Aggelos K. Katsaggelos:
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO. CoRR abs/1911.01915 (2019) - [i4]Alice Lucas
Self-Supervised Fine-tuning for Image Enhancement of Super-Resolution Deep Neural Networks. CoRR abs/1912.12879 (2019) - 2018
- [j60]Salvador Villena, Miguel Vega
Image super-resolution for outdoor digital forensics. Usability and legal aspects. Comput. Ind. 98: 34-47 (2018) - [j59]Santiago Lopez Tapia, Rafael Molina
Using machine learning to detect and localize concealed objects in passive millimeter-wave images. Eng. Appl. Artif. Intell. 67: 81-90 (2018) - [j58]Neda Rohani
Variational Gaussian process for multisensor classification problems. Pattern Recognit. Lett. 116: 80-87 (2018) - [j57]Alice Lucas
Using Deep Neural Networks for Inverse Problems in Imaging: Beyond Analytical Methods. IEEE Signal Process. Mag. 35(1): 20-36 (2018) - [j56]Pablo Morales-Alvarez
Remote Sensing Image Classification With Large-Scale Gaussian Processes. IEEE Trans. Geosci. Remote. Sens. 56(2): 1103-1114 (2018) - [c113]Adrián Colomer
Hard Exudate Detection Using Local Texture Analysis and Gaussian Processes. ICIAR 2018: 639-649 - [c112]Alice Lucas, Aggelos K. Katsaggelos
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. ICIP 2018: 51-55 - [c111]Natalia Hidalgo-Gavira, Javier Mateos
Blind Color Deconvolution of Histopathological Images Using a Variational Bayesian Approach. ICIP 2018: 983-987 - [c110]Daniel Heestermans Svendsen, Pablo Morales-Alvarez
Deep Gaussian Processes for Geophysical Parameter Retrieval. IGARSS 2018: 6175-6178 - [c109]Natalia Hidalgo-Gavira, Javier Mateos
Fully Automated Blind Color Deconvolution of Histopathological Images. MICCAI (2) 2018: 183-191 - [i3]Alice Lucas, Santiago Lopez Tapia, Rafael Molina, Aggelos K. Katsaggelos:
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. CoRR abs/1806.05764 (2018) - 2017
- [j55]Xu Zhou
Fast Bayesian blind deconvolution with Huber Super Gaussian priors. Digit. Signal Process. 60: 122-133 (2017) - [j54]Michael Iliadis, Haohong Wang, Rafael Molina
Robust and Low-Rank Representation for Fast Face Identification With Occlusions. IEEE Trans. Image Process. 26(5): 2203-2218 (2017) - [j53]Juan G. Serra
Bayesian K-SVD Using Fast Variational Inference. IEEE Trans. Image Process. 26(7): 3344-3359 (2017) - [c108]Juan G. Serra, Javier Mateos
Parameter estimation in spike and slab variational inference for blind image deconvolution. EUSIPCO 2017: 1495-1499 - [c107]Pablo Morales-Alvarez
Passive millimeter wave image classification with large scale Gaussian processes. ICIP 2017: 370-374 - [c106]Juan G. Serra, Salvador Villena, Rafael Molina
Greedy Bayesian double sparsity dictionary learning. ICIP 2017: 1935-1939 - [c105]Juan G. Serra, Javier Mateos
Spike and slab variational inference for blind image deconvolution. ICIP 2017: 3765-3769 - [c104]Pablo Morales-Alvarez
Efficient remote sensing image classification with Gaussian processes and Fourier features. IGARSS 2017: 2227-2230 - [i2]Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls:
Remote Sensing Image Classification with Large Scale Gaussian Processes. CoRR abs/1710.00575 (2017) - 2016
- [j52]Wael AlSaafin
Compressive sensing super resolution from multiple observations with application to passive millimeter wave images. Digit. Signal Process. 50: 180-190 (2016) - [j51]Pablo Ruiz Matarán
Joint Data Filtering and Labeling Using Gaussian Processes and Alternating Direction Method of Multipliers. IEEE Trans. Image Process. 25(7): 3059-3072 (2016) - [c103]Wael Saafin
Compressed sensing super resolution of color images. EUSIPCO 2016: 1563-1567 - [c102]Emre Besler, Pablo Ruiz
Classification of multiple annotator data using variational Gaussian process inference. EUSIPCO 2016: 2025-2029 - [c101]Santiago Lopez Tapia, Rafael Molina
Detection and localization of objects in Passive Millimeter Wave Images. EUSIPCO 2016: 2101-2105 - [c100]Juan G. Serra, Pablo Ruiz
Bayesian logistic regression with sparse general representation prior for multispectral image classification. ICIP 2016: 1893-1897 - [c99]Javier Mateos
Multiframe blind deconvolution of passive millimeter wave images using variational dirichlet blur kernel estimation. ICIP 2016: 2678-2682 - [c98]Pablo Ruiz
Variational Gaussian process for missing label crowdsourcing classification problems. MLSP 2016: 1-6 - [i1]Michael Iliadis, Haohong Wang, Rafael Molina, Aggelos K. Katsaggelos:
Robust and Low-Rank Representation for Fast Face Identification with Occlusions. CoRR abs/1605.02266 (2016) - 2015
- [j50]Pablo Ruiz
Variational Bayesian Blind Image Deconvolution: A review. Digit. Signal Process. 47: 116-127 (2015) - [j49]Aggelos K. Katsaggelos
Audiovisual Fusion: Challenges and New Approaches. Proc. IEEE 103(9): 1635-1653 (2015) - [j48]Xu Zhou
Variational Dirichlet Blur Kernel Estimation. IEEE Trans. Image Process. 24(12): 5127-5139 (2015) - [j47]Zhaofu Chen, Rafael Molina
Robust Recovery of Temporally Smooth Signals From Under-Determined Multiple Measurements. IEEE Trans. Signal Process. 63(7): 1779-1791 (2015) - [c97]Neda Rohani, Pablo Ruiz
Variational Gaussian process for sensor fusion. EUSIPCO 2015: 170-174 - [c96]I. Gomez Maqueda, Nicolas Pérez de la Blanca, Rafael Molina
Fast millimeter wave threat detection algorithm. EUSIPCO 2015: 599-603 - [c95]Wael Saafin
PMMW image super resolution from compressed sensing observations. EUSIPCO 2015: 1815-1819 - [c94]Wael Saafin
Image super-resolution from compressed sensing observations. ICIP 2015: 4268-4272 - 2014
- [j46]Salvador Villena, Miguel Vega
A non-stationary image prior combination in super-resolution. Digit. Signal Process. 32: 1-10 (2014) - [j45]Martin Luessi, S. Derin Babacan, Rafael Molina
Variational Bayesian causal connectivity analysis for fMRI. Frontiers Neuroinformatics 8: 45 (2014) - [j44]Pablo Ruiz
Combining Poisson singular integral and total variation prior models in image restoration. Signal Process. 103: 296-308 (2014) - [j43]Zhaofu Chen, Rafael Molina
Automated Recovery of Compressedly Observed Sparse Signals From Smooth Background. IEEE Signal Process. Lett. 21(8): 1012-1016 (2014) - [j42]Pablo Ruiz
Bayesian Active Remote Sensing Image Classification. IEEE Trans. Geosci. Remote. Sens. 52(4): 2186-2196 (2014) - [j41]Lei Song, Fan Jiang, Zhongke Shi, Rafael Molina
Toward Dynamic Scene Understanding by Hierarchical Motion Pattern Mining. IEEE Trans. Intell. Transp. Syst. 15(3): 1273-1285 (2014) - [j40]Zhaofu Chen, S. Derin Babacan, Rafael Molina
Variational Bayesian Methods For Multimedia Problems. IEEE Trans. Multim. 16(4): 1000-1017 (2014) - [c93]Ana Illanas, Faraón Llorens, Rafael Molina, Francisco Gallego, Patricia Compañ, Rosana Satorre, Carlos Villagrá:
¿Puede un videojuego ayudarnos a predecir los resultados de aprendizaje? CoSECivi 2014: 11-22 - [c92]Zhaofu Chen, Rafael Molina, Aggelos K. Katsaggelos:
Recovery of correlated sparse signals from under-sampled measurements. EUSIPCO 2014: 451-455 - [c91]Pablo Ruiz, Nicolas Pérez de la Blanca, Rafael Molina, Aggelos K. Katsaggelos:
Bayesian classification and active learning using lp-priors. Application to image segmentation. EUSIPCO 2014: 1183-1187 - [c90]Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos:
Parameter estimation in Bayesian Blind Deconvolution with super Gaussian image priors. EUSIPCO 2014: 1632-1636 - [c89]Xu Zhou
Fast iteratively reweighted least squares for lp regularized image deconvolution and reconstruction. ICIP 2014: 1783-1787 - [c88]Pablo Ruiz
Learning filters in Gaussian process classification problems. ICIP 2014: 2913-2917 - [c87]Faraón Llorens
Technological Ecosystem for Open Education. IDT/IIMSS/STET 2014: 706-715 - 2013
- [j39]Salvador Villena, Miguel Vega
Bayesian combination of sparse and non-sparse priors in image super resolution. Digit. Signal Process. 23(2): 530-541 (2013) - [j38]Miguel Tallon, Javier Mateos
Space-variant blur deconvolution and denoising in the dual exposure problem. Inf. Fusion 14(4): 396-409 (2013) - [j37]Zhaofu Chen, Rafael Molina
A Variational Approach for Sparse Component Estimation and Low-Rank Matrix Recovery. J. Commun. 8(9): 600-611 (2013) - [j36]Bruno Amizic, Leonidas Spinoulas, Rafael Molina
Compressive Blind Image Deconvolution. IEEE Trans. Image Process. 22(10): 3994-4006 (2013) - [j35]Martin Luessi, S. Derin Babacan, Rafael Molina
Bayesian Simultaneous Sparse Approximation With Smooth Signals. IEEE Trans. Signal Process. 61(22): 5716-5729 (2013) - [c86]Bruno Amizic, Leonidas Spinoulas, Rafael Molina, Aggelos K. Katsaggelos:
Variational Bayesian compressive blind image deconvolution. EUSIPCO 2013: 1-5 - [c85]Hiram Madero Orozco, Pablo Ruiz, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos:
Image deblurring combining poisson singular integral and total variation prior models. EUSIPCO 2013: 1-5 - [c84]Jorge Rubio, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos:
A general sparse image prior combination in Compressed Sensing. EUSIPCO 2013: 1-5 - [c83]Pablo Ruiz, Javier Mateos, María C. Cárdenas, Shinichi Nakajima, Rafael Molina, Aggelos K. Katsaggelos:
Light field acquisition from blurred observations using a programmable coded aperture camera. EUSIPCO 2013: 1-5 - [c82]Salvador Villena, Miguel Vega
A general sparse image prior combination in super-resolution. DSP 2013: 1-6 - [p1]Pablo Ruiz
Interactive Pansharpening and Active Classification in Remote Sensing. Multimodal Interaction in Image and Video Applications 2013: 67-81 - 2012
- [j34]Bruno Amizic, Rafael Molina
Sparse Bayesian blind image deconvolution with parameter estimation. EURASIP J. Image Video Process. 2012: 20 (2012) - [j33]S. Derin Babacan, Reto Ansorge, Martin Luessi, Pablo Ruiz Matarán
Compressive Light Field Sensing. IEEE Trans. Image Process. 21(12): 4746-4757 (2012) - [j32]S. Derin Babacan, Martin Luessi, Rafael Molina
Sparse Bayesian Methods for Low-Rank Matrix Estimation. IEEE Trans. Signal Process. 60(8): 3964-3977 (2012) - [c81]S. Derin Babacan, Rafael Molina
Bayesian Blind Deconvolution with General Sparse Image Priors. ECCV (6) 2012: 341-355 - [c80]Miguel Tallon, S. Derin Babacan, Javier Mateos, Minh N. Do, Rafael Molina, Aggelos K. Katsaggelos:
Upsampling and denoising of depth maps via joint-segmentation. EUSIPCO 2012: 245-249 - [c79]Antonio López, Jesús M. Cortés, Domingo López-Oller, Rafael Molina, Aggelos K. Katsaggelos:
Hyperparameters estimation for the Bayesian localization of the EEG sources with TV priors. EUSIPCO 2012: 489-493 - [c78]Leonidas Spinoulas, Bruno Amizic, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos:
Simultaneous Bayesian compressive sensing and blind deconvolution. EUSIPCO 2012: 1414-1418 - [c77]Bruno Amizic, Leonidas Spinoulas, Rafael Molina
Compressive sampling with unknown blurring function: Application to passive millimeter-wave imaging. ICIP 2012: 925-928 - 2011
- [j31]Israa Amro
A survey of classical methods and new trends in pansharpening of multispectral images. EURASIP J. Adv. Signal Process. 2011: 79 (2011) - [j30]Martin Luessi, S. Derin Babacan, Rafael Molina
Bayesian symmetrical EEG/fMRI fusion with spatially adaptive priors. NeuroImage 55(1): 113-132 (2011) - [j29]S. Derin Babacan, Rafael Molina
Variational Bayesian Super Resolution. IEEE Trans. Image Process. 20(4): 984-999 (2011) - [j28]Miguel Vega
Super Resolution of Multispectral Images using ℓ1 Image Models and Interband Correlations. J. Signal Process. Syst. 65(3): 509-523 (2011) - [c76]Bruno Amizic, Rafael Molina, Aggelos K. Katsaggelos:
Bayesian partial out-of-focus blur removal with parameter estimation. EUSIPCO 2011: 1673-1677 - [c75]Miguel Tallon, Javier Mateos, S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Space-variant kernel deconvolution for dual exposure problem. EUSIPCO 2011: 1678-1682 - [c74]S. Derin Babacan, Martin Luessi, Rafael Molina
Low-rank matrix completion by variational sparse Bayesian learning. ICASSP 2011: 2188-2191 - [c73]Miguel Vega
Bayesian TV denoising of SAR images. ICIP 2011: 165-168 - [c72]Esteban Vera
A novel iterative image restoration algorithm using nonstationary image priors. ICIP 2011: 3457-3460 - [c71]Pablo Ruiz
Video retrieval using sparse Bayesian reconstruction. ICME 2011: 1-6 - [c70]Miguel Tallon, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos:
Image prior combination in space-variant blur deconvolution for the dual exposure problem. ISPA 2011: 408-413 - [c69]Pablo Ruiz, S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Retrieval of video clips with missing frames using sparse Bayesian reconstruction. ISPA 2011: 443-448 - [c68]Pablo Ruiz
A Bayesian Active Learning Framework for a Two-Class Classification Problem. MUSCLE 2011: 42-53 - 2010
- [j27]S. Derin Babacan, Rafael Molina
Bayesian Compressive Sensing Using Laplace Priors. IEEE Trans. Image Process. 19(1): 53-63 (2010) - [j26]Giannis K. Chantas, Nikolas P. Galatsanos, Rafael Molina
Variational Bayesian Image Restoration With a Product of Spatially Weighted Total Variation Image Priors. IEEE Trans. Image Process. 19(2): 351-362 (2010) - [j25]S. Derin Babacan, Jingnan Wang, Rafael Molina
Bayesian Blind Deconvolution From Differently Exposed Image Pairs. IEEE Trans. Image Process. 19(11): 2874-2888 (2010) - [c67]Giannis K. Chantas, Nikolaos Galatsanos, Rafael Molina
Variational Bayesian inference image restoration using a product of total variation-like image priors. CIP 2010: 227-231 - [c66]Miguel Tallon, Javier Mateos, S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Combining observation models in dual exposure problems using the Kullback-Leibler divergence. EUSIPCO 2010: 323-327 - [c65]Salvador Villena, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos:
Image prior combination in super-resolution image reconstruction. EUSIPCO 2010: 616-620 - [c64]Bruno Amizic, S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Sparse Bayesian blind image deconvolution with parameter estimation. EUSIPCO 2010: 626-630 - [c63]Martin Luessi, S. Derin Babacan, Rafael Molina
Symmetrical EEG/FMRI fusion with spatially adaptive priors using variational distribution approximation. ICASSP 2010: 638-641 - [c62]Bruno Amizic, S. Derin Babacan, Michael K. Ng
Fast total variation image restoration with parameter estimation using bayesian inference. ICASSP 2010: 770-773 - [c61]Salvador Villena, Miguel Vega
Using the Kullback-Leibler divergence to combine image priors in Super-Resolution image reconstruction. ICIP 2010: 893-896 - [c60]S. Derin Babacan, Rafael Molina
Sparse Bayesian image restoration. ICIP 2010: 3577-3580
2000 – 2009
- 2009
- [j24]Miguel Vega
Super-Resolution of Multispectral Images. Comput. J. 52(1): 153-167 (2009) - [j23]Aggelos K. Katsaggelos
Guest Editorial. Comput. J. 52(4): 395-396 (2009) - [j22]S. Derin Babacan, Rafael Molina
Variational Bayesian Blind Deconvolution Using a Total Variation Prior. IEEE Trans. Image Process. 18(1): 12-26 (2009) - [c59]Salvador Villena, Miguel Vega
Parameter Estimation in Bayesian Super-Resolution Image Reconstruction from Low Resolution Rotated and Translated Images. ACIVS 2009: 188-199 - [c58]S. Derin Babacan, Luis Mancera, Rafael Molina, Aggelos K. Katsaggelos:
Non-convex priors in Bayesian compressed sensing. EUSIPCO 2009: 110-114 - [c57]S. Derin Babacan, Rafael Molina
Fast bayesian compressive sensing using Laplace priors. ICASSP 2009: 2873-2876 - [c56]Miguel Vega, Rafael Molina
L1 prior majorization in Bayesian image restoration. DPS 2009: 1-6 - [c55]Javier Mateos
Local Bayesian image restoration using variational methods and Gamma-Normal distributions. ICIP 2009: 129-132 - [c54]S. Derin Babacan, Jingnan Wang, Rafael Molina
Bayesian blind deconvolution from differently exposed image pairs. ICIP 2009: 133-136 - [c53]S. Derin Babacan, Reto Ansorge, Martin Luessi, Rafael Molina
Compressive sensing of light fields. ICIP 2009: 2337-2340 - [c52]Luis Mancera, S. Derin Babacan, Rafael Molina
Image restoration by mixture modelling of an overcomplete linear representation. ICIP 2009: 3949-3952 - 2008
- [j21]S. Derin Babacan, Rafael Molina
Parameter Estimation in TV Image Restoration Using Variational Distribution Approximation. IEEE Trans. Image Process. 17(3): 326-339 (2008) - [c51]S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Parameter estimation in total variation blind deconvolution. EUSIPCO 2008: 1-5 - [c50]S. Derin Babacan, Rafael Molina
Generalized Gaussian Markov random field image restoration using variational distribution approximation. ICASSP 2008: 1265-1268 - [c49]S. Derin Babacan, Rafael Molina
Total variation super resolution using a variational approach. ICIP 2008: 641-644 - [c48]Tom E. Bishop, Rafael Molina
Blind restoration of blurred photographs via AR modelling and MCMC. ICIP 2008: 669-672 - [c47]Miguel Vega, Javier Mateos, Rafael Molina
Super Resolution of Multispectral Images Using TV Image Models. KES (3) 2008: 408-415 - [c46]Bruno Amizic, Aggelos K. Katsaggelos, Rafael Molina:
Using Logarithmic Opinion Pooling Techniques in Bayesian Blind Multi-Channel Restoration. VISAPP (1) 2008: 565-570 - 2007
- [b1]Aggelos K. Katsaggelos
Super Resolution of Images and Video. Synthesis Lectures on Image, Video, and Multimedia Processing, Morgan & Claypool Publishers 2007, ISBN 978-3-031-01115-3 - [j20]Dácil Barreto, Luis D. Alvarez, Rafael Molina
Region-based super-resolution for compression. Multidimens. Syst. Signal Process. 18(2-3): 59-81 (2007) - [c45]Antonio Javier Gallego
3D Reconstruction and Mapping from Stereo Pairs with Geometrical Rectification. BVAI 2007: 318-327 - [c44]Antonio Javier Gallego
Rectified Reconstruction from Stereo Pairs and Robot Mapping. CAIP 2007: 141-148 - [c43]Rafael Molina, Javier Mateos, Miguel Vega, Aggelos K. Katsaggelos:
Super resolution of multispectral images using locally adaptive models. EUSIPCO 2007: 1497-1501 - [c42]S. Derin Babacan, Rafael Molina, Aggelos K. Katsaggelos:
Total variation blind deconvolution using a variational approach to parameter, image, and blur estimation. EUSIPCO 2007: 2164-2168 - [c41]S. Derin Babacan, Rafael Molina
Total Variation Image Restoration and Parameter Estimation using Variational Posterior Distribution Approximation. ICIP (1) 2007: 97-100 - [c40]Rafael Molina
From Global to Local Bayesian Parameter Estimation in Image Restoration using Variational Distribution Approximations. ICIP (1) 2007: 121-124 - [c39]Tom E. Bishop, Rafael Molina
Nonstationary Blind Image Restoration using Variational Methods. ICIP (1) 2007: 125-128 - [c38]Rafael Molina, Antonio López, José Manuel Martín, Aggelos K. Katsaggelos:
Variational posterior distribution approximation in bayesian emission tomography reconstruction using a gamma mixture prior. VISAPP (Special Sessions) 2007: 165-176 - 2006
- [j19]Miguel Vega
A Bayesian Super-Resolution Approach to Demosaicing of Blurred Images. EURASIP J. Adv. Signal Process. 2006 (2006) - [j18]Rafael Molina
Blind Deconvolution Using a Variational Approach to Parameter, Image, and Blur Estimation. IEEE Trans. Image Process. 15(12): 3715-3727 (2006) - [c37]Rafael Molina, Miguel Vega, Javier Mateos, Aggelos K. Katsaggelos:
Hierarchical Bayesian super resolution reconstruction of multispectral images. EUSIPCO 2006: 1-5 - [c36]Antonio López, José Manuel Martín
Transmission Tomography Reconstruction Using Compound Gauss-Markov Random Fields and Ordered Subsets. ICIAR (2) 2006: 559-569 - [c35]Rafael Molina
Parameter Estimation in Bayesian Reconstruction of Multispectral Images using Super Resolution Techniques. ICIP 2006: 1749-1752 - [c34]Pilar Arques, Rafael Molina, Mar Pujol, Ramón Rizo:
Distance histogram to centroid as a unique feature to recognize objects. VISAPP (1) 2006: 492-500 - 2005
- [c33]Fidel Aznar Gregori, Mireia Sempere, Mar Pujol, Ramón Rizo, Rafael Molina
3D Robot Mapping: Combining Active and Non Active Sensors in a Probabilistic Framework. CAEPIA 2005: 11-20 - [c32]Miguel Vega, Rafael Molina
Bayesian Reconstruction of Color Images Acquired with a Single CCD. IbPRIA (1) 2005: 343-350 - [c31]Antonio López, Rafael Molina
Bayesian Reconstruction for Transmission Tomography with Scale Hyperparameter Estimation. IbPRIA (2) 2005: 455-462 - [c30]Javier Mateos
Approximations of posterior distributions in blind deconvolution using variational methods. ICIP (2) 2005: 770-773 - 2004
- [j17]Antonio López, Rafael Molina
Parameter estimation in Bayesian reconstruction of SPECT images: An aid in nuclear medicine diagnosis. Int. J. Imaging Syst. Technol. 14(1): 21-27 (2004) - [j16]Luis D. Alvarez, Javier Mateos
High-resolution images from compressed low-resolution video: Motion estimation and observable pixels. Int. J. Imaging Syst. Technol. 14(2): 58-66 (2004) - [j15]C. Andrew Segall, Aggelos K. Katsaggelos
Bayesian resolution enhancement of compressed video. IEEE Trans. Image Process. 13(7): 898-911 (2004) - [c29]Salvador Villena, Javier Abad, Rafael Molina
Estimation of High Resolution Images and Registration Parameters from Low Resolution Observations. CIARP 2004: 509-516 - [c28]Luis D. Alvarez, Rafael Molina, Aggelos K. Katsaggelos:
Motion estimation in high resolution image reconstruction from compressed video sequences. ICIP 2004: 1795-1798 - 2003
- [j14]C. Andrew Segall, Rafael Molina
High-resolution images from low-resolution compressed video. IEEE Signal Process. Mag. 20(3): 37-48 (2003) - [j13]Rafael Molina
Bayesian multichannel image restoration using compound Gauss-Markov random fields. IEEE Trans. Image Process. 12(12): 1642-1654 (2003) - [j12]Rafael Molina
Parameter estimation in Bayesian high-resolution image reconstruction with multisensors. IEEE Trans. Image Process. 12(12): 1655-1667 (2003) - [c27]Luis D. Alvarez, Rafael Molina
Multi-channel Reconstruction of Video Sequences from Low-Resolution and Compressed Observations. CIARP 2003: 46-53 - [c26]Antonio López, Rafael Molina
Bayesian SPECT Image Reconstruction with Scale Hyperparameter Estimation for Scalable Prior. IbPRIA 2003: 445-452 - [c25]Javier Mateos, Miguel Vega, Rafael Molina
Bayesian Image Estimation from an Incomplete Set of Blurred, Undersampled Low Resolution Images. IbPRIA 2003: 538-546 - [c24]Javier Mateos, Rafael Molina
Bayesian high resolution image reconstruction with incomplete multisensor low resolution systems. ICASSP (3) 2003: 705-708 - [c23]Javier Abad, Miguel Vega, Rafael Molina
Parameter estimation in super-resolution image reconstruction problems. ICASSP (3) 2003: 709-712 - [c22]Miguel Vega, Javier Mateos, Rafael Molina
Bayesian parameter estimation in image reconstruction from subsampled blurred observations. ICIP (2) 2003: 969-972 - [c21]Francisco J. Cortijo, Salvador Villena, Rafael Molina
Bayesian super-resolution of text image sequences from low resolution observations. ISSPA (1) 2003: 421-424 - 2002
- [j11]Antonio López, Rafael Molina
SPECT Image Reconstruction Using Compound Prior Models. Int. J. Pattern Recognit. Artif. Intell. 16(3): 317-330 (2002) - [c20]C. Andrew Segall, Rafael Molina, Aggelos K. Katsaggelos
Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations. ICASSP 2002: 1701-1704 - [c19]Antonio López, Rafael Molina
Scale hyperparameter estimation for GGMRF prior models with application to SPECT images. DSP 2002: 521-524 - [c18]Rafael Molina
A General Multichannel Image Restoration Method Using Compound Models. ICPR (3) 2002: 835-838 - 2001
- [j10]Rafael Molina
Image restoration in astronomy: a Bayesian perspective. IEEE Signal Process. Mag. 18(2): 11-29 (2001) - [c17]Antonio López, Rafael Molina
SPECT image reconstruction using compound models. ICASSP 2001: 1909-1912 - [c16]Rafael Molina
Bayesian high-resolution reconstruction of low-resolution compressed video. ICIP (2) 2001: 25-28 - 2000
- [j9]Rafael Molina
Restoration of severely blurred high range images using stochastic and deterministic relaxation algorithms in compound Gauss?CMarkov random fields. Pattern Recognit. 33(4): 555-571 (2000) - [j8]Javier Mateos
A Bayesian approach for the estimation and transmission of regularization parameters for reducing blocking artifacts. IEEE Trans. Image Process. 9(7): 1200-1215 (2000) - [j7]Nikolas P. Galatsanos, Vladimir Z. Mesarovic, Rafael Molina
Hierarchical Bayesian image restoration from partially known blurs. IEEE Trans. Image Process. 9(10): 1784-1797 (2000) - [c15]Javier Mateos, Aggelos K. Katsaggelos, Rafael Molina:
Color image restoration using compound Gauss-Markov Random Fields. EUSIPCO 2000: 1-4 - [c14]Javier Mateos, Aggelos K. Katsaggelos, Rafael Molina:
High-resolution color image reconstruction from compressed video sequences. EUSIPCO 2000: 1-4 - [c13]Rafael Molina
Multichannel image restoration using compound Gauss-Markov random fields. ICASSP 2000: 141-144 - [c12]Javier Mateos, Aggelos K. Katsaggelos
Resolution enhancement of compressed low resolution video. ICASSP 2000: 1919-1922 - [c11]Javier Mateos, Aggelos K. Katsaggelos
Simultaneous Motion Estimation and Resolution Enhancement of Compressed low Resolution Video. ICIP 2000: 653-656
1990 – 1999
- 1999
- [j6]Rafael Molina
Bayesian and regularization methods for hyperparameter estimation in image restoration. IEEE Trans. Image Process. 8(2): 231-246 (1999) - [c10]Rafael Molina
Bayesian image restoration using a wavelet-based subband decomposition. ICASSP 1999: 3257-3260 - [c9]Antonio López, Rafael Molina, Aggelos K. Katsaggelos
Hyperparameter Estimation for Emission Computed Tomography Data. ICIP (2) 1999: 677-680 - 1998
- [c8]Vladimir Z. Mesarovic, Nikolas P. Galatsanos, Rafael Molina
Hierarchical Bayesian image restoration from partially-known blurs. ICASSP 1998: 2905-2908 - [c7]Javier Mateos, Carlos Ilia Herráiz Montalvo, Blas C. Ruiz Jiménez, Rafael Molina
Reduction of Blocking Artifacts in Block Transformed Compressed Color Images. ICIP (1) 1998: 401-405 - 1997
- [c6]Rafael Molina
Restoration of Severely Blurred High Range Images Using Stochastic and Deterministic Relaxation Algorithms in Compound Gauss Markov Random Fields. EMMCVPR 1997: 117-132 - [c5]Rafael Molina
A Bayesian approach to blind deconvolution based on Dirichlet distributions. ICASSP 1997: 2809-2812 - 1996
- [c4]Rafael Molina
Restoration of severely blurred high range images using compound models. ICIP (2) 1996: 469-472 - 1995
- [j5]Rafael Molina
Bayesian image restoration in astronomy: Application to images of the recent collision of comet shoemaker-levy 9 with jupiter. Int. J. Imaging Syst. Technol. 6(4): 370-375 (1995) - [j4]Jose A. García, J. Fdez-Valdivia
A method for invariant pattern recognition using the scale-vector representation of planar curves. Signal Process. 43(1): 39-53 (1995) - [j3]Jose A. García, J. Fdez-Valdivia
A dynamic approach for clustering data. Signal Process. 44(2): 181-196 (1995) - 1994
- [j2]Rafael Molina
On the Hierarchical Bayesian Approach to Image Restoration: Applications to Astronomical Images. IEEE Trans. Pattern Anal. Mach. Intell. 16(11): 1122-1128 (1994) - [j1]Jose A. García, Rafael Molina
Automatic characterization of spiral and elliptical galaxies from digital images. Pattern Recognit. Lett. 15(9): 861-869 (1994) - 1992
- [c3]Rafael Molina
On the Bayesian deconvolution of planets. ICPR (3) 1992: 147-150 - [c2]A. Sutherland, Bob Henery, Rafael Molina, Charles C. Taylor, Ross D. King:
Statistical Methods in Learning. IPMU 1992: 173-182 - 1991
- [c1]Silvia Acid, Luis M. de Campos
Learning with CASTLE. ECSQARU 1991: 99-106
Coauthor Index
Nicolas Pérez de la Blanca
aka: Nicolás Pérez de la Blanca
aka: Nicolás Pérez de la Blanca
[j97] [j94] [j92] [j91] [j90] [j88] [c133] [i18] [i17] [i16] [i15] [j86] [j84] [j83] [c131] [c129] [c128] [c127] [i12] [j79] [j78] [j77] [j75] [j74] [c125] [j71] [j70] [j69] [j68] [c124] [c123] [c122] [j65] [j64] [j63] [j61] [c121] [c120] [c119] [c118] [c117] [c116] [c115] [i6] [i5] [i4] [j60] [j58] [j57] [c113] [c112] [c111] [c109] [i3] [j55] [j54] [j53] [c108] [c107] [c106] [c105] [j52] [j51] [c103] [c102] [c100] [c99] [c98] [i1] [j50] [j49] [j48] [j47] [c97] [c96] [c95] [c94] [j46] [j45] [j44] [j43] [j42] [j41] [j40] [c92] [c91] [c90] [c89] [c88] [j39] [j38] [j37] [j36] [j35] [c86] [c85] [c84] [c83] [c82] [p1] [j34] [j33] [j32] [c81] [c80] [c79] [c78] [c77] [j31] [j30] [j29] [j28] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [j27] [j26] [j25] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [j24] [j23] [j22] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [j21] [c51] [c50] [c49] [c47] [c46] [b1] [j20] [c43] [c42] [c41] [c40] [c38] [j19] [j18] [c37] [c36] [c35] [c32] [c31] [c30] [j17] [j16] [j15] [c29] [c28] [j14] [j13] [j12] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [j11] [c20] [c19] [c18] [c17] [c16] [j9] [j8] [j7] [c15] [c14] [c13] [c12] [c11] [j6] [c10] [c9] [c8] [c7] [c6] [c5] [c4]
[j93] [c133] [j85] [j84] [c128] [j79] [j71] [j69] [j68] [j65] [c120] [j60] [c111] [c109] [c108] [c105] [c99] [j50] [j48] [j44] [j42] [c88] [j38] [c85] [c83] [p1] [c80] [j31] [j28] [c75] [c73] [c70] [c68] [c66] [j24] [c55] [c47] [b1] [c43] [j18] [c37] [c35] [c30] [j16] [j15] [j13] [c25] [c24] [c22] [j11] [c20] [c18] [j10] [c17] [c16] [j9] [j8] [c15] [c14] [c13] [c12] [c11] [j6] [c7] [c6] [c5] [c4] [j5]
Pablo Morales-Alvarez
aka: Pablo Morales-Álvarez
aka: Pablo Morales-Álvarez
Pablo Ruiz 0002
aka: Pablo Ruiz Matarán
aka: Pablo Ruiz Matarán
Santiago Lopez Tapia
aka: Santiago López-Tapia
aka: Santiago López-Tapia
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