CardioGRID: a framework for the analysis of cardiological signals in GRID computing. - Marcelo R. Risk; Francisco Prieto Castrillo; Juan Francisco Garcia Eijo; Cesar Suarez Ortega; María Botón-Fernández; Alfonso Pardo Diaz; Manuel Rubio del Solar; Raúl Ramos-Pollán (LANOMS, 2009)

Introducing ROC Curves as Error Measure Functions: A New Approach to Train ANN-Based Biomedical Data Classifiers. - Raúl Ramos-Pollán; Miguel Ángel Guevara-López; Eugénio C. Oliveira (CIARP, 2010)

Bioingenium at ImageCLEF 2012: Text and Visual Indexing for Medical Images. - Jorge A. Vanegas; Juan C. Caicedo; Jorge E. Camargo; Raúl Ramos-Pollán; Fabio A. González 001 (CLEF (Online Working Notes/Labs/Workshop), 2012)

BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. - Raúl Ramos-Pollán; Fabio A. González 001; Juan C. Caicedo; Angel Cruz-Roa; Jorge E. Camargo; Jorge A. Vanegas; Santiago A. Perez; José David Bermeo; Juan Sebastian Otálora Montenegro; Paola K. Rozo; John Edison Arevalo Ovalle (eScience, 2012)

Exchanging Data for Breast Cancer Diagnosis on Heterogeneous Grid Platforms. - Damià Segrelles; Ignacio Blanquer; José Salavert Torres; Vicente Hernández; Jose Miguel Franco-Valiente; Guillermo Díaz-Herrero; Raúl Ramos-Pollán; Rosana Medina; Luis Martí-Bonmatí; Miguel Ángel Guevara-López; Naymi González; Joana Loureiro; et al. (Comput. Informatics, 2012)

A Software Framework for Building Biomedical Machine Learning Classifiers through Grid Computing Resources. - Raúl Ramos-Pollán; Miguel Ángel Guevara-López; Eugénio C. Oliveira (J. Medical Syst., 2012)

Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis. - Raúl Ramos-Pollán; Miguel Ángel Guevara-López; Cesar Suarez Ortega; Guillermo Díaz-Herrero; Jose Miguel Franco-Valiente; Manuel Rubio del Solar; Naimy González-de-Posada; Mário Augusto Pires Vaz; Joana Loureiro; Isabel Ramos (J. Medical Syst., 2012)

Benchmarking Datasets for Breast Cancer Computer-Aided Diagnosis (CADx). - Daniel Cardoso Moura; Miguel Ángel Guevara-López; Pedro Cunha; Naimy González-de-Posada; Raúl Ramos-Pollán; Isabel Ramos; Joana Pinheiro Loureiro; Inês C. Moreira; Bruno M. Ferreira de Araújo; Teresa Cardoso Fernandes (CIARP (1), 2013)

Distributed Cache Strategies for Machine Learning Classification Tasks over Cluster Computing Resources. - John Edison Arevalo Ovalle; Raúl Ramos-Pollán; Fabio A. González 001 (CARLA, 2014)

Classification of Low-Level Atmospheric Structures Based on a Pyramid Representation and a Machine Learning Method. - Sebastián Sierra; Juan F. Molina; Angel Cruz-Roa; José Daniel Pabón; Raúl Ramos-Pollán; Fabio A. González 001; Hugo Franco (CIARP, 2015)

Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides. - Francy Camacho; Rodrigo Torres; Raúl Ramos-Pollán (CMSB, 2015)

Convolutional neural networks for mammography mass lesion classification. - John Edison Arevalo Ovalle; Fabio A. González 001; Raúl Ramos-Pollán; José Luís Oliveira; Miguel Ángel Guevara-López (EMBC, 2015)

Supervised Greedy Layer-Wise Training for Deep Convolutional Networks with Small Datasets. - Diego Rueda-Plata; Raúl Ramos-Pollán; Fabio A. González 001 (ICCCI (1), 2015)

On the Representativeness of Convolutional Neural Networks Layers. - Dario Garcia-Gasulla; Jonathan Moreno; Raúl Ramos-Pollán; Romel Casadiegos Barrios; Javier Béjar; Ulises Cortés; Eduard Ayguadé; Jesús Labarta; Toyotaro Suzumura (CCIA, 2016)

Data driven Vertical Total Electron Content workflow for GNSS positioning for single frequency receivers. - Susana Sanchez-Naranjo; Fabio A. González 001; Raúl Ramos-Pollán; Marc Solé (ICL-GNSS, 2016)

Representation learning for mammography mass lesion classification with convolutional neural networks. - John Edison Arevalo Ovalle; Fabio A. González 001; Raúl Ramos-Pollán; José Luís Oliveira; Miguel Ángel Guevara-López (Comput. Methods Programs Biomed., 2016)

Effective training of convolutional neural networks with small, specialized datasets. - Diego Rueda-Plata; Raúl Ramos-Pollán; Fabio A. González 001 (J. Intell. Fuzzy Syst., 2017)

Deep Learning Applied to Steganalysis of Digital Images: A Systematic Review. - Reinel Tabares-Soto; Raúl Ramos-Pollán; Gustavo A. Isaza (IEEE Access, 2019)

GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis. - Reinel Tabares-Soto; Harold Brayan Arteaga-Arteaga; Mario Alejandro Bravo-Ortiz; Alejandro Mora-Rubio; Daniel Arias-Garzón; Jesús Alejandro Alzate-Grisales; Alejandro Buenaventura Burbano-Jacome; Simon Orozco-Arias; Gustavo A. Isaza; Raúl Ramos-Pollán (IEEE Access, 2021)

Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain. - Reinel Tabares-Soto; Harold Brayan Arteaga-Arteaga; Alejandro Mora-Rubio; Mario Alejandro Bravo-Ortiz; Daniel Arias-Garzón; Jesús Alejandro Alzate-Grisales; Alejandro Buenaventura Burbano-Jacome; Simon Orozco-Arias; Gustavo A. Isaza; Raúl Ramos-Pollán (PeerJ Comput. Sci., 2021)

Sensitivity of deep learning applied to spatial image steganalysis. - Reinel Tabares-Soto; Harold Brayan Arteaga-Arteaga; Alejandro Mora-Rubio; Mario Alejandro Bravo-Ortiz; Daniel Arias-Garzón; Jesús Alejandro Alzate-Grisales; Simon Orozco-Arias; Gustavo A. Isaza; Raúl Ramos-Pollán (PeerJ Comput. Sci., 2021)

Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy. - Miguel Plazas; Raúl Ramos-Pollán; Fabian León; Fabio Martínez (Image Processing, 2022)

Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

SAR-based landslide classification pretraining leads to better segmentation. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

Deep learning based landslide density estimation on SAR data for rapid response. - Vanessa Boehm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

A Contrastive Method Based on Elevation Data for Remote Sensing with Scarce and High Level Semantic Labels. - Omar A. Castaño-Idarraga; Raúl Ramos-Pollán; Freddie Kalaitzis (CoRR, 2023)

Quantum Kernel Mixtures for Probabilistic Deep Learning. - Fabio A. González 001; Raúl Ramos-Pollán; Joseph A. Gallego-Mejia (CoRR, 2023)

Lightweight learning from label proportions on satellite imagery. - Raúl Ramos-Pollán; Fabio A. González 001 (CoRR, 2023)

Fewshot learning on global multimodal embeddings for earth observation tasks. - Matt Allen 001; Francisco Dorr; Joseph A. Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data. - Matt Allen 001; Francisco Dorr; Joseph A. Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction. - Laura Martínez-Ferrer; Anna Jungbluth; Joseph A. Gallego-Mejia; Matt Allen 001; Francisco Dorr; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery. - Joseph A. Gallego-Mejia; Anna Jungbluth; Laura Martínez-Ferrer; Matt Allen 001; Francisco Dorr; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2023)

A two-stage data-driven metaheuristic to predict last-mile delivery route sequences. - Juan Pablo Mesa; Alejandro Montoya; Raúl Ramos-Pollán; Mauricio Toro (Eng. Appl. Artif. Intell., 2023)

Sentinel2 RGB chips over BENELUX with ESA World Cover for Learning with Label Proportions. - Raúl Ramos-Pollán; Fabio A. González 001 (Zenodo, 2023)

Sentinel2 RGB chips over Colombia (NE) with ESA World Cover for Learning with Label Proportions. - Raúl Ramos-Pollán; Fabio A. González 001 (Zenodo, 2023)

Sentinel2 RGB chips over Colombia (NE) with JRC GHSL Population Density 2015 for Learning with Label Proportions. - Raúl Ramos-Pollán; Fabio A. González 001 (Zenodo, 2023)

Sentinel2 RGB chips over BENELUX with JRC GHSL Population Density 2015 for Learning with Label Proportions. - Raúl Ramos-Pollán; Fabio A. González 001 (Zenodo, 2023)

Learning with Label Proportions on Sentinel-2 RGB imagery. - Raúl Ramos-Pollán; Fabio Augusto González Osorio (IEEE DataPort, 2023)

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data. - Matthew J. Allen 001; Francisco Dorr; Joseph Alejandro Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (NeurIPS, 2024)

A Bi-Objective Approach to Last-Mile Delivery Routing Considering Driver Preferences. - Juan Pablo Mesa; Alejandro Montoya; Raúl Ramos-Pollán; Mauricio Toro (CoRR, 2024)

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data. - Matthew J. Allen 001; Francisco Dorr; Joseph Alejandro Gallego-Mejia; Laura Martínez-Ferrer; Anna Jungbluth; Freddie Kalaitzis; Raúl Ramos-Pollán (CoRR, 2024)

Uncertainty and Generalizability in Foundation Models for Earth Observation. - Raúl Ramos-Pollán; Freddie Kalaitzis; Karthick Panner Selvam (CoRR, 2024)

Rapid Adaptation of Earth Observation Foundation Models for Segmentation. - Karthick Panner Selvam; Raúl Ramos-Pollán; Freddie Kalaitzis (CoRR, 2024)

A Foundation Model for the Solar Dynamics Observatory. - James Walsh 008; Daniel G. Gass; Raúl Ramos-Pollán; Paul J. Wright; Richard Galvez; Noah Kasmanoff; Jason Naradowsky; Anne Spalding; James Parr; Atilim Günes Baydin (CoRR, 2024)

Machine-learning component for multi-start metaheuristics to solve the capacitated vehicle routing problem. - Juan Pablo Mesa; Alejandro Montoya; Raúl Ramos-Pollán; Mauricio Toro (Appl. Soft Comput., 2025)