Rafael Molina 0001 - researchr alias

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2024

Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological imagesPablo Morales Álvarez, Arne Schmidt 0005, José Miguel Hernández-Lobato, Rafael Molina 0001. PR, 146:110057, February 2024. [doi]

2023

Probabilistic fusion of crowds and experts for the search of gravitational wavesPablo Ruiz 0002, Pablo Morales Álvarez, Scott Coughlin, Rafael Molina 0001, Aggelos K. Katsaggelos. kbs, 261:110183, 2023. [doi]

Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image SegmentationArne Schmidt 0005, Pablo Morales Álvarez, Rafael Molina 0001. iccv 2023: 21040-21049 [doi]

Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN datasetRocío del Amor, Jose Pérez-Cano, Miguel López-Pérez, Liria Terradez, José Aneiros-Fernández, Sandra Morales, Javier Mateos, Rafael Molina 0001, Valery Naranjo. artmed, 145:102686, November 2023. [doi]

Crowdsourcing Segmentation of Histopathological Images Using Annotations Provided by Medical StudentsMiguel López-Pérez, Pablo Morales Álvarez, Lee A. D. Cooper, Rafael Molina 0001, Aggelos K. Katsaggelos. aime 2023: 245-249 [doi]

Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue ClassificationMiguel López-Pérez, Pablo Morales Álvarez, Lee A. D. Cooper, Rafael Molina 0001, Aggelos K. Katsaggelos. access, 11:6922-6934, 2023. [doi]

Deep Robust Image Restoration Using the Moore-Penrose Blur InverseSantiago López-Tapia, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. icip 2023: 775-779 [doi]

Learning Moore-Penrose based residuals for robust non-blind image deconvolutionSantiago López-Tapia, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. dsp, 142:104193, October 2023. [doi]

A Robust BKSVD Method for Blind Color Deconvolution and Blood Detection on H &E Histological ImagesFernando Pérez-Bueno, Kjersti Engan, Rafael Molina 0001. aime 2023: 207-217 [doi]

Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage DetectionYunan Wu, Francisco M. Castro-Macías, Pablo Morales Álvarez, Rafael Molina 0001, Aggelos K. Katsaggelos. miccai 2023: 327-337 [doi]

Deep Bayesian Blind Color Deconvolution of Histological ImagesShuowen Yang, Fernando Pérez-Bueno, Francisco M. Castro-Macías, Rafael Molina 0001, Aggelos K. Katsaggelos. icip 2023: 710-714 [doi]

2022

Efficient Cancer Classification by Coupling Semi Supervised and Multiple Instance LearningArne Schmidt 0005, Julio Silva-Rodríguez, Rafael Molina 0001, Valery Naranjo. access, 10:9763-9773, 2022. [doi]

The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A ReviewNeel Kanwal, Fernando Pérez-Bueno, Arne Schmidt 0005, Kjersti Engan, Rafael Molina 0001. access, 10:58821-58844, 2022. [doi]

Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detectionMiguel López-Pérez, Arne Schmidt 0005, Yunan Wu, Rafael Molina 0001, Aggelos K. Katsaggelos. cmpb, 219:106783, 2022. [doi]

Leveraging a Probabilistic PCA Model to Understand the Multivariate Statistical Network Monitoring Framework for Network Security Anomaly DetectionFernando Pérez-Bueno, Luz García 0001, Gabriel Maciá-Fernández, Rafael Molina 0001. ton, 30(3):1217-1229, 2022. [doi]

Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classificationFernando Pérez-Bueno, Juan G. Serra, Miguel Vega, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. cmig, 97:102048, 2022. [doi]

Proportion constrained weakly supervised histopathology image classificationJulio Silva-Rodríguez, Arne Schmidt 0005, María Á. Sales, Rafael Molina 0001, Valery Naranjo. cbm, 147:105714, 2022. [doi]

Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGOPablo Morales Álvarez, Pablo Ruiz 0002, Scott Coughlin, Rafael Molina 0001, Aggelos K. Katsaggelos. pami, 44(3):1534-1551, 2022. [doi]

2021

A Contribution to Deep Learning Approaches for Automatic Classification of Volcano-Seismic Events: Deep Gaussian ProcessesMiguel López-Pérez, Luz García, M. Carmen Benítez, Rafael Molina 0001. tgrs, 59(5):3875-3890, 2021. [doi]

Deep learning approaches to inverse problems in imaging: Past, present and futureSantiago López-Tapia, Rafael Molina 0001, Aggelos K. Katsaggelos. dsp, 119:103285, 2021. [doi]

Activation-level uncertainty in deep neural networksPablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina 0001, José Miguel Hernández-Lobato. iclr 2021: [doi]

Blind color deconvolution, normalization, and classification of histological images using general super Gaussian priors and Bayesian inferenceFernando Pérez-Bueno, Miguel Vega, María Á. Sales, José Aneiros-Fernández, Valery Naranjo, Rafael Molina 0001, Aggelos K. Katsaggelos. cmpb, 211:106453, 2021. [doi]

Combining Attention-Based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage DetectionYunan Wu, Arne Schmidt, Enrique Hernández-Sánchez, Rafael Molina 0001, Aggelos K. Katsaggelos. miccai 2021: 582-591 [doi]

2020

Variational Bayesian Blind Color Deconvolution of Histopathological ImagesNatalia Hidalgo-Gavira, Javier Mateos, Miguel Vega, Rafael Molina 0001, Aggelos K. Katsaggelos. TIP, 29:2026-2036, 2020. [doi]

Gated Recurrent Networks for Video Super ResolutionSantiago López-Tapia, Alice Lucas, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2020: 700-704 [doi]

A single video super-resolution GAN for multiple downsampling operators based on pseudo-inverse image formation modelsSantiago López-Tapia, Alice Lucas, Rafael Molina 0001, Aggelos K. Katsaggelos. dsp, 104:102801, 2020. [doi]

Fully Automatic Blind Color Deconvolution of Histological Images Using Super GaussiansFernando Pérez-Bueno, Miguel Vega, Valery Naranjo, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2020: 1254-1258 [doi]

Super Gaussian Priors for Blind Color Deconvolution of Histological ImagesFernando Pérez-Bueno, Miguel Vega, Valery Naranjo, Rafael Molina 0001, Aggelos K. Katsaggelos. icip 2020: 3010-3014 [doi]

A TV-based image processing framework for blind color deconvolution and classification of histological imagesFernando Pérez-Bueno, Miguel López-Pérez, Miguel Vega, Javier Mateos, Valery Naranjo, Rafael Molina 0001, Aggelos K. Katsaggelos. dsp, 101:102727, 2020. [doi]

Variational Bayesian Pansharpening with Super-Gaussian Sparse Image PriorsFernando Pérez-Bueno, Miguel Vega, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. sensors, 20(18):5308, 2020. [doi]

Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detectionJulio Silva-Rodríguez, Adrián Colomer, María Á. Sales, Rafael Molina 0001, Valery Naranjo. cmpb, 195:105637, 2020. [doi]

Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield MicroscopyXu Zhou, Rafael Molina 0001, Yi Ma, Tianfu Wang, Dong Ni. TIP, 29:3227-3238, 2020. [doi]

2019

Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging ProblemsAlice Lucas, Santiago López-Tapia, Rafael Molina 0001, Aggelos K. Katsaggelos. icip 2019: 3591-3595 [doi]

Classifying Prostate Histological Images Using Deep Gaussian Processes on a New Optical Density Granulometry-Based DescriptorMiguel López-Pérez, Adrián Colomer, María Á. Sales, Rafael Molina 0001, Valery Naranjo. ideal 2019: 39-46 [doi]

Gan-Based Video Super-Resolution With Direct Regularized Inversion of the Low-Resolution Formation ModelSantiago López-Tapia, Alice Lucas, Rafael Molina 0001, Aggelos K. Katsaggelos. icip 2019: 2886-2890 [doi]

Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation ModelSantiago Lopez Tapia, Alice Lucas, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2019: 1-5 [doi]

Variational Bayes Color Deconvolution with a Total Variation PriorMiguel Vega, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2019: 1-5 [doi]

A Composite Discriminator for Generative Adversarial Network based Video Super-ResolutionXijun Wang, Alice Lucas, Santiago Lopez Tapia, Xinyi Wu, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2019: 1-5 [doi]

Semantic Prior Based Generative Adversarial Network for Video Super-ResolutionXinyi Wu, Alice Lucas, Santiago López-Tapia, Xijun Wang, Yul Hee Kim, Rafael Molina 0001, Aggelos K. Katsaggelos. eusipco 2019: 1-5 [doi]

2011

Retrieval of video clips with missing frames using sparse Bayesian reconstructionPablo Ruiz 0002, S. Derin Babacan, Rafael Molina 0001, Aggelos K. Katsaggelos. imspa 2011: 443-448 [doi]

Image prior combination in space-variant blur deconvolution for the dual exposure problemMiguel Tallon, Javier Mateos, Rafael Molina 0001, Aggelos K. Katsaggelos. imspa 2011: 408-413 [doi]

2009

L1 prior majorization in Bayesian image restorationMiguel Vega, Rafael Molina 0001, Aggelos K. Katsaggelos. icdsp 2009: 1-6 [doi]

2003

High-resolution images from low-resolution compressed videoC. Andrew Segall, Rafael Molina 0001, Aggelos K. Katsaggelos. spm, 20(3):37-48, 2003. [doi]

2002

Scale hyperparameter estimation for GGMRF prior models with application to SPECT imagesAntonio López, Rafael Molina 0001, Aggelos K. Katsaggelos. icdsp 2002: 521-524 [doi]

2001

Image restoration in astronomy: a Bayesian perspectiveRafael Molina 0001, Jorge Núñez, Francisco J. Cortijo, Javier Mateos. spm, 18(2):11-29, 2001. [doi]

1992

On the Bayesian deconvolution of planetsRafael Molina 0001, B. D. Ripley, Francisco J. Cortijo. icpr 1992: 147-150 [doi]

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2011

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2002

2001

1992

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