Raúl Ramos-Pollán

43 papers A* 1B 1C 2Journal 28Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Kernel density matrices for probabilistic deep learning. Quantum Mach. Intell. Fabio A. González, Raúl Ramos-Pollán, Joseph A. Gallego-Mejia
2025	J	`jnl`	Machine-learning component for multi-start metaheuristics to solve the capacitated vehicle routing problem. Appl. Soft Comput. Juan Pablo Mesa, Alejandro Montoya, Raúl Ramos-Pollán, Mauricio Toro
2025	J	`jnl`	Publisher Correction: Kernel density matrices for probabilistic deep learning. Quantum Mach. Intell. Fabio A. González, Raúl Ramos-Pollán, Joseph Gallego
2024	J	`jnl`	A Bi-Objective Approach to Last-Mile Delivery Routing Considering Driver Preferences. CoRR Juan Pablo Mesa, Alejandro Montoya, Raúl Ramos-Pollán, Mauricio Toro
2024	J	`jnl`	A Foundation Model for the Solar Dynamics Observatory. CoRR James Walsh, Daniel G. Gass, Raúl Ramos-Pollán, Paul J. Wright, Richard Galvez, Noah Kasmanoff, Jason Naradowsky, Anne Spalding, James Parr, Atilim Günes Baydin
2024	A*	`conf`	M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data. NeurIPS Matthew J. Allen, Francisco Dorr, Joseph Alejandro Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
2024	J	`jnl`	M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data. CoRR Matthew J. Allen, Francisco Dorr, Joseph Alejandro Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
2024	J	`jnl`	Rapid Adaptation of Earth Observation Foundation Models for Segmentation. CoRR Karthick Panner Selvam, Raúl Ramos-Pollán, Freddie Kalaitzis
2024	J	`jnl`	Uncertainty and Generalizability in Foundation Models for Earth Observation. CoRR Raúl Ramos-Pollán, Freddie Kalaitzis, Karthick Panner Selvam
2023	J	`jnl`	A Contrastive Method Based on Elevation Data for Remote Sensing with Scarce and High Level Semantic Labels. CoRR Omar A. Castaño-Idarraga, Raúl Ramos-Pollán, Freddie Kalaitzis
2023	J	`jnl`	A two-stage data-driven metaheuristic to predict last-mile delivery route sequences. Eng. Appl. Artif. Intell. Juan Pablo Mesa, Alejandro Montoya, Raúl Ramos-Pollán, Mauricio Toro
2023	J	`jnl`	Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery. CoRR Joseph A. Gallego-Mejia, Anna Jungbluth, Laura Martínez-Ferrer, Matt Allen, Francisco Dorr, Freddie Kalaitzis, Raúl Ramos-Pollán
2023	J	`jnl`	Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction. CoRR Laura Martínez-Ferrer, Anna Jungbluth, Joseph A. Gallego-Mejia, Matt Allen, Francisco Dorr, Freddie Kalaitzis, Raúl Ramos-Pollán
2023	J	`jnl`	Fewshot learning on global multimodal embeddings for earth observation tasks. CoRR Matt Allen, Francisco Dorr, Joseph A. Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
2023	J	`jnl`	Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data. CoRR Matt Allen, Francisco Dorr, Joseph A. Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
2023	J	`jnl`	Lightweight learning from label proportions on satellite imagery. CoRR Raúl Ramos-Pollán, Fabio A. González
2023	J	`jnl`	Quantum Kernel Mixtures for Probabilistic Deep Learning. CoRR Fabio A. González, Raúl Ramos-Pollán, Joseph A. Gallego-Mejia
2022	J	`jnl`	Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. CoRR Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
2022	J	`jnl`	Deep learning based landslide density estimation on SAR data for rapid response. CoRR Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
2022	J	`jnl`	SAR-based landslide classification pretraining leads to better segmentation. CoRR Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
2022	B	`conf`	Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy. Image Processing Miguel Plazas, Raúl Ramos-Pollán, Fabian León, Fabio Martínez
2021	J	`jnl`	GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis. IEEE Access 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
2021	J	`jnl`	Sensitivity of deep learning applied to spatial image steganalysis. PeerJ Comput. Sci. 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
2021	J	`jnl`	Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain. PeerJ Comput. Sci. 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
2019	J	`jnl`	Deep Learning Applied to Steganalysis of Digital Images: A Systematic Review. IEEE Access Reinel Tabares-Soto, Raúl Ramos-Pollán, Gustavo A. Isaza
2019	—	`ed.`	High Performance Computing - 5th Latin American Conference, CARLA 2018, Bucaramanga, Colombia, September 26-28, 2018, Revised Selected Papers CARLA Esteban Meneses, Harold Castro, Carlos Jaime Barrios Hernández, Raúl Ramos-Pollán
2017	J	`jnl`	Effective training of convolutional neural networks with small, specialized datasets. J. Intell. Fuzzy Syst. Diego Rueda-Plata, Raúl Ramos-Pollán, Fabio A. González
2016	—	`conf`	Data driven Vertical Total Electron Content workflow for GNSS positioning for single frequency receivers. ICL-GNSS Susana Sanchez-Naranjo, Fabio A. González, Raúl Ramos-Pollán, Marc Solé
2016	—	`conf`	On the Representativeness of Convolutional Neural Networks Layers. CCIA Dario Garcia-Gasulla, Jonathan Moreno, Raúl Ramos-Pollán, Romel Casadiegos Barrios, Javier Béjar, Ulises Cortés, Eduard Ayguadé, Jesús Labarta, Toyotaro Suzumura
2016	J	`jnl`	Representation learning for mammography mass lesion classification with convolutional neural networks. Comput. Methods Programs Biomed. John Edison Arevalo Ovalle, Fabio A. González, Raúl Ramos-Pollán, José Luís Oliveira, Miguel Ángel Guevara-López
2015	C	`conf`	Classification of Low-Level Atmospheric Structures Based on a Pyramid Representation and a Machine Learning Method. CIARP Sebastián Sierra, Juan F. Molina, Angel Cruz-Roa, José Daniel Pabón, Raúl Ramos-Pollán, Fabio A. González, Hugo Franco
2015	—	`conf`	Convolutional neural networks for mammography mass lesion classification. EMBC John Edison Arevalo Ovalle, Fabio A. González, Raúl Ramos-Pollán, José Luís Oliveira, Miguel Ángel Guevara-López
2015	—	`conf`	Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides. CMSB Francy Camacho, Rodrigo Torres, Raúl Ramos-Pollán
2015	—	`conf`	Supervised Greedy Layer-Wise Training for Deep Convolutional Networks with Small Datasets. ICCCI (1) Diego Rueda-Plata, Raúl Ramos-Pollán, Fabio A. González
2014	—	`conf`	Distributed Cache Strategies for Machine Learning Classification Tasks over Cluster Computing Resources. CARLA John Edison Arevalo Ovalle, Raúl Ramos-Pollán, Fabio A. González
2013	—	`conf`	Benchmarking Datasets for Breast Cancer Computer-Aided Diagnosis (CADx). CIARP (1) 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
2012	J	`jnl`	A Software Framework for Building Biomedical Machine Learning Classifiers through Grid Computing Resources. J. Medical Syst. Raúl Ramos-Pollán, Miguel Ángel Guevara-López, Eugénio C. Oliveira
2012	—	`conf`	BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. eScience Raúl Ramos-Pollán, Fabio A. González, 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
2012	—	`conf`	Bioingenium at ImageCLEF 2012: Text and Visual Indexing for Medical Images. CLEF (Online Working Notes/Labs/Workshop) Jorge A. Vanegas, Juan C. Caicedo, Jorge E. Camargo, Raúl Ramos-Pollán, Fabio A. González
2012	J	`jnl`	Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis. J. Medical Syst. 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
2012	J	`jnl`	Exchanging Data for Breast Cancer Diagnosis on Heterogeneous Grid Platforms. Comput. Informatics 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, Isabel Ramos
2010	C	`conf`	Introducing ROC Curves as Error Measure Functions: A New Approach to Train ANN-Based Biomedical Data Classifiers. CIARP Raúl Ramos-Pollán, Miguel Ángel Guevara-López, Eugénio C. Oliveira
2009	—	`conf`	CardioGRID: a framework for the analysis of cardiological signals in GRID computing. LANOMS 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