Rafael Molina

ORCID

Publication Activity (10 Years)

Years Active: 1991-2024
Publications (10 Years): 103

Top Venues

CoRR

EUSIPCO

ICIP

Digit. Signal Process.

Publications

Jose Pérez-Cano, Yunan Wu, Arne Schmidt, Miguel López-Pérez, Pablo Morales-Álvarez, Rafael Molina, Aggelos K. Katsaggelos
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 (2024)
Neel Kanwal, Miguel López-Pérez, Umay Kiraz, Tahlita C. M. Zuiverloon, Rafael Molina, Kjersti Engan
Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images. Comput. Medical Imaging Graph. 112 (2024)
Miguel López-Pérez, Pablo Morales-Álvarez, Lee A. D. Cooper, Christopher Felicelli, Jeffery Goldstein, Brian Vadasz, Rafael Molina, Aggelos K. Katsaggelos
Learning from crowds for automated histopathological image segmentation. Comput. Medical Imaging Graph. 112 (2024)
Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina
Probabilistic Attention Based on Gaussian Processes for Deep Multiple Instance Learning. IEEE Trans. Neural Networks Learn. Syst. 35 (8) (2024)
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 (2024)
Shuowen Yang, Fernando Pérez-Bueno, Francisco M. Castro-Macías, Rafael Molina, Aggelos K. Katsaggelos
BCD-net: Stain separation of histological images using deep variational Bayesian blind color deconvolution. Digit. Signal Process. 145 (2024)
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 (2024)
Francisco M. Castro-Macías, Pablo Morales-Álvarez, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection. Artif. Intell. 331 (2024)
Francisco M. Castro-Macías, Pablo Morales-Álvarez, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection. CoRR (2024)
Arne Schmidt, Pablo Morales-Álvarez, Lee A. D. Cooper, Lee A. Newberg, Andinet Enquobahrie, Rafael Molina, Aggelos K. Katsaggelos
Focused active learning for histopathological image classification. Medical Image Anal. 95 (2024)
Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation. ICCV (2023)
Santiago López-Tapia, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Deep Robust Image Restoration Using the Moore-Penrose Blur Inverse. ICIP (2023)
Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation. CoRR (2023)
Shuowen Yang, Fernando Pérez-Bueno, Francisco M. Castro-Macías, Rafael Molina, Aggelos K. Katsaggelos
Deep Bayesian Blind Color Deconvolution of Histological Images. ICIP (2023)
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 (2023)
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. MICCAI (5) (2023)
Miguel López-Pérez, Pablo Morales-Álvarez, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos
Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification. IEEE Access 11 (2023)
Fernando Pérez-Bueno, Luz García, Gabriel Maciá-Fernández, Rafael Molina
Leveraging a Probabilistic PCA Model to Understand the Multivariate Statistical Network Monitoring Framework for Network Security Anomaly Detection. CoRR (2023)
Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina
Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning. CoRR (2023)
Santiago López-Tapia, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Learning Moore-Penrose based residuals for robust non-blind image deconvolution. Digit. Signal Process. 142 (2023)
Fernando Pérez-Bueno, Kjersti Engan, Rafael Molina
A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H &E Histological Images. AIME (2023)
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 (2023)
Miguel López-Pérez, Pablo Morales-Álvarez, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos
Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical Students. AIME (2023)
Pablo Ruiz, Pablo Morales-Álvarez, Scott Coughlin, Rafael Molina, Aggelos K. Katsaggelos
Probabilistic fusion of crowds and experts for the search of gravitational waves. Knowl. Based Syst. 261 (2023)
Rocío del Amor, Jose Pérez-Cano, Miguel López-Pérez, Liria Terradez, José Aneiros-Fernández, Sandra Morales, Javier Mateos, Rafael Molina, Valery Naranjo
Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset. Artif. Intell. Medicine 145 (2023)
Neel Kanwal, Fernando Pérez-Bueno, Arne Schmidt, Kjersti Engan, Rafael Molina
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 (2022)
Fernando Pérez-Bueno, Juan G. Serra, Miguel Vega, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification. Comput. Medical Imaging Graph. 97 (2022)
Arne Schmidt, Julio Silva-Rodríguez, Rafael Molina, Valery Naranjo
Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance Learning. IEEE Access 10 (2022)
Miguel López-Pérez, Arne Schmidt, Yunan Wu, Rafael Molina, Aggelos K. Katsaggelos
Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection. Comput. Methods Programs Biomed. 219 (2022)
Julio Silva-Rodríguez, Arne Schmidt, María Á. Sales, Rafael Molina, Valery Naranjo
Proportion constrained weakly supervised histopathology image classification. Comput. Biol. Medicine 147 (2022)
Fernando Pérez-Bueno, Luz García, Gabriel Maciá-Fernández, Rafael Molina
Leveraging a Probabilistic PCA Model to Understand the Multivariate Statistical Network Monitoring Framework for Network Security Anomaly Detection. IEEE/ACM Trans. Netw. 30 (3) (2022)
Pablo Morales-Álvarez, Pablo Ruiz, Scott Coughlin, Rafael Molina, Aggelos K. Katsaggelos
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Fernando Pérez-Bueno, Miguel Vega, María Á. Sales, José Aneiros-Fernández, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
Blind color deconvolution, normalization, and classification of histological images using general super Gaussian priors and Bayesian inference. Comput. Methods Programs Biomed. 211 (2021)
Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández-Lobato
Activation-level uncertainty in deep neural networks. ICLR (2021)
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 (2021)
Miguel López-Pérez, Luz García, M. Carmen Benítez, Rafael Molina
A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian Processes. IEEE Trans. Geosci. Remote. Sens. 59 (5) (2021)
Santiago López-Tapia, Rafael Molina, Aggelos K. Katsaggelos
Deep learning approaches to inverse problems in imaging: Past, present and future. Digit. Signal Process. 119 (2021)
Yunan Wu, Arne Schmidt, Enrique Hernández-Sánchez, Rafael Molina, Aggelos K. Katsaggelos
Combining Attention-Based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection. MICCAI (2) (2021)
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 (2021)
Xu Zhou, Rafael Molina, Yi Ma, Tianfu Wang, Dong Ni
Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy. IEEE Trans. Image Process. 29 (2020)
Natalia Hidalgo-Gavira, Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Variational Bayesian Blind Color Deconvolution of Histopathological Images. IEEE Trans. Image Process. 29 (2020)
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. Comput. Methods Programs Biomed. 195 (2020)
Fernando Pérez-Bueno, Miguel Vega, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
Super Gaussian Priors for Blind Color Deconvolution of Histological Images. ICIP (2020)
Daniel Heestermans Svendsen, Pablo Morales-Álvarez, Rafael Molina, Gustau Camps-Valls
Deep Gaussian Processes for geophysical parameter retrieval. CoRR (2020)
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. Digit. Signal Process. 104 (2020)
Santiago López-Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos
Gated Recurrent Networks for Video Super Resolution. EUSIPCO (2020)
Fernando Pérez-Bueno, Miguel López-Pérez, Miguel Vega, Javier Mateos, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
A TV-based image processing framework for blind color deconvolution and classification of histological images. Digit. Signal Process. 101 (2020)
Fernando Pérez-Bueno, Miguel Vega, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Variational Bayesian Pansharpening with Super-Gaussian Sparse Image Priors. Sensors 20 (18) (2020)
Fernando Pérez-Bueno, Miguel Vega, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
Fully Automatic Blind Color Deconvolution of Histological Images Using Super Gaussians. EUSIPCO (2020)
Xijun Wang, Alice Lucas, Santiago Lopez Tapia, Xinyi Wu, Rafael Molina, Aggelos K. Katsaggelos
A Composite Discriminator for Generative Adversarial Network based Video Super-Resolution. EUSIPCO (2019)
Ángel E. Esteban, Miguel López-Pérez, Adrián Colomer, María Á. Sales, Rafael Molina, Valery Naranjo
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 (2019)
Alice Lucas, Santiago López-Tapia, Rafael Molina, Aggelos K. Katsaggelos
Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging Problems. ICIP (2019)
Xijun Wang, Alice Lucas, Santiago Lopez Tapia, Xinyi Wu, Rafael Molina, Aggelos K. Katsaggelos
Spatially Adaptive Losses for Video Super-resolution with GANs. ICASSP (2019)
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 (2019)
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)
Miguel López-Pérez, Adrián Colomer, María Á. Sales, Rafael Molina, Valery Naranjo
Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based Descriptor. IDEAL (1) (2019)
Juan G. Serra, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Variational EM method for blur estimation using the spike-and-slab image prior. Digit. Signal Process. 88 (2019)
Xinyi Wu, Alice Lucas, Santiago López-Tapia, Xijun Wang, Yul Hee Kim, Rafael Molina, Aggelos K. Katsaggelos
Semantic Prior Based Generative Adversarial Network for Video Super-Resolution. EUSIPCO (2019)
Pablo Morales-Alvarez, Pablo Ruiz, Scott Coughlin, Rafael Molina, Aggelos K. Katsaggelos
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO. CoRR (2019)
Santiago Lopez Tapia, Alice Lucas, Rafael Molina, Aggelos K. Katsaggelos
Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation Model. EUSIPCO (2019)
Santiago López-Tapia, Rafael Molina, Nicolás Pérez de la Blanca
Deep CNNs for Object Detection Using Passive Millimeter Sensors. IEEE Trans. Circuits Syst. Video Technol. 29 (9) (2019)
Alice Lucas, Santiago Lopez Tapia, Rafael Molina, Aggelos K. Katsaggelos
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. IEEE Trans. Image Process. 28 (7) (2019)
Pablo Morales-Alvarez, Pablo Ruiz, Raúl Santos-Rodríguez, Rafael Molina, Aggelos K. Katsaggelos
Scalable and efficient learning from crowds with Gaussian processes. Inf. Fusion 52 (2019)
Pablo Ruiz, Pablo Morales-Alvarez, Rafael Molina, Aggelos K. Katsaggelos
Learning from crowds with variational Gaussian processes. Pattern Recognit. 88 (2019)
Alice Lucas, Santiago Lopez Tapia, Rafael Molina, Aggelos K. Katsaggelos
Self-Supervised Fine-tuning for Image Enhancement of Super-Resolution Deep Neural Networks. CoRR (2019)
Miguel Vega, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Variational Bayes Color Deconvolution with a Total Variation Prior. EUSIPCO (2019)
Salvador Villena, Miguel Vega, Javier Mateos, Duska Rosenberg, Fionn Murtagh, Rafael Molina, Aggelos K. Katsaggelos
Image super-resolution for outdoor digital forensics. Usability and legal aspects. Comput. Ind. 98 (2018)
Daniel Heestermans Svendsen, Pablo Morales-Alvarez, Rafael Molina, Gustau Camps-Valls
Deep Gaussian Processes for Geophysical Parameter Retrieval. IGARSS (2018)
Natalia Hidalgo-Gavira, Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Blind Color Deconvolution of Histopathological Images Using a Variational Bayesian Approach. ICIP (2018)
Natalia Hidalgo-Gavira, Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Fully Automated Blind Color Deconvolution of Histopathological Images. MICCAI (2) (2018)
Santiago Lopez Tapia, Rafael Molina, Nicolas Pérez de la Blanca
Using machine learning to detect and localize concealed objects in passive millimeter-wave images. Eng. Appl. Artif. Intell. 67 (2018)
Alice Lucas, Aggelos K. Katsaggelos, Santiago Lopez Tapia, Rafael Molina
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. ICIP (2018)
Alice Lucas, Michael Iliadis, Rafael Molina, Aggelos K. Katsaggelos
Using Deep Neural Networks for Inverse Problems in Imaging: Beyond Analytical Methods. IEEE Signal Process. Mag. 35 (1) (2018)
Alice Lucas, Santiago Lopez Tapia, Rafael Molina, Aggelos K. Katsaggelos
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution. CoRR (2018)
Adrián Colomer, Pablo Ruiz, Valery Naranjo, Rafael Molina, Aggelos K. Katsaggelos
Hard Exudate Detection Using Local Texture Analysis and Gaussian Processes. ICIAR (2018)
Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls
Remote Sensing Image Classification With Large-Scale Gaussian Processes. IEEE Trans. Geosci. Remote. Sens. 56 (2) (2018)
Neda Rohani, Pablo Ruiz, Rafael Molina, Aggelos K. Katsaggelos
Variational Gaussian process for multisensor classification problems. Pattern Recognit. Lett. 116 (2018)
Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls, Aggelos K. Katsaggelos
Passive millimeter wave image classification with large scale Gaussian processes. ICIP (2017)
Juan G. Serra, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Parameter estimation in spike and slab variational inference for blind image deconvolution. EUSIPCO (2017)
Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls
Efficient remote sensing image classification with Gaussian processes and Fourier features. IGARSS (2017)
Michael Iliadis, Haohong Wang, Rafael Molina, Aggelos K. Katsaggelos
Robust and Low-Rank Representation for Fast Face Identification With Occlusions. IEEE Trans. Image Process. 26 (5) (2017)
Juan G. Serra, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Spike and slab variational inference for blind image deconvolution. ICIP (2017)
Juan G. Serra, Matteo Testa, Rafael Molina, Aggelos K. Katsaggelos
Bayesian K-SVD Using Fast Variational Inference. IEEE Trans. Image Process. 26 (7) (2017)
Xu Zhou, Miguel Vega, Fugen Zhou, Rafael Molina, Aggelos K. Katsaggelos
Fast Bayesian blind deconvolution with Huber Super Gaussian priors. Digit. Signal Process. 60 (2017)
Juan G. Serra, Salvador Villena, Rafael Molina, Aggelos K. Katsaggelos
Greedy Bayesian double sparsity dictionary learning. ICIP (2017)
Pablo Morales-Alvarez, Adrian Perez-Suay, Rafael Molina, Gustau Camps-Valls
Remote Sensing Image Classification with Large Scale Gaussian Processes. CoRR (2017)
Pablo Ruiz, Emre Besler, Rafael Molina, Aggelos K. Katsaggelos
Variational Gaussian process for missing label crowdsourcing classification problems. MLSP (2016)
Emre Besler, Pablo Ruiz, Rafael Molina, Aggelos K. Katsaggelos
Classification of multiple annotator data using variational Gaussian process inference. EUSIPCO (2016)
Wael Saafin, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Compressed sensing super resolution of color images. EUSIPCO (2016)
Javier Mateos, Antonio López, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Multiframe blind deconvolution of passive millimeter wave images using variational dirichlet blur kernel estimation. ICIP (2016)
Michael Iliadis, Haohong Wang, Rafael Molina, Aggelos K. Katsaggelos
Robust and Low-Rank Representation for Fast Face Identification with Occlusions. CoRR (2016)
Juan G. Serra, Pablo Ruiz, Rafael Molina, Aggelos K. Katsaggelos
Bayesian logistic regression with sparse general representation prior for multispectral image classification. ICIP (2016)
Pablo Ruiz Matarán, Rafael Molina, Aggelos K. Katsaggelos
Joint Data Filtering and Labeling Using Gaussian Processes and Alternating Direction Method of Multipliers. IEEE Trans. Image Process. 25 (7) (2016)
Wael AlSaafin, Salvador Villena, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Compressive sensing super resolution from multiple observations with application to passive millimeter wave images. Digit. Signal Process. 50 (2016)
Santiago Lopez Tapia, Rafael Molina, Nicolas Pérez de la Blanca
Detection and localization of objects in Passive Millimeter Wave Images. EUSIPCO (2016)
Aggelos K. Katsaggelos, Sara Bahaadini, Rafael Molina
Audiovisual Fusion: Challenges and New Approaches. Proc. IEEE 103 (9) (2015)
Wael Saafin, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
Image super-resolution from compressed sensing observations. ICIP (2015)
Pablo Ruiz, Xu Zhou, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos
Variational Bayesian Blind Image Deconvolution: A review. Digit. Signal Process. 47 (2015)
I. Gomez Maqueda, Nicolas Pérez de la Blanca, Rafael Molina, Aggelos K. Katsaggelos
Fast millimeter wave threat detection algorithm. EUSIPCO (2015)
Wael Saafin, Salvador Villena, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
PMMW image super resolution from compressed sensing observations. EUSIPCO (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rafael Molina