Raúl Ramos-Pollán

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 18

Top Topics

Synthetic Aperture Radar

Top Venues

Eng. Appl. Artif. Intell.

Publications

Juan Pablo Mesa, Alejandro Montoya, Raúl Ramos-Pollán, Mauricio Toro
A Bi-Objective Approach to Last-Mile Delivery Routing Considering Driver Preferences. CoRR (2024)
Matthew J. Allen, Francisco Dorr, Joseph Alejandro Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data. CoRR (2024)
Laura Martínez-Ferrer, Anna Jungbluth, Joseph A. Gallego-Mejia, Matt Allen, Francisco Dorr, Freddie Kalaitzis, Raúl Ramos-Pollán
Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction. CoRR (2023)
Matt Allen, Francisco Dorr, Joseph A. Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data. CoRR (2023)
Matt Allen, Francisco Dorr, Joseph A. Gallego-Mejia, Laura Martínez-Ferrer, Anna Jungbluth, Freddie Kalaitzis, Raúl Ramos-Pollán
Fewshot learning on global multimodal embeddings for earth observation tasks. CoRR (2023)
Juan Pablo Mesa, Alejandro Montoya, Raúl Ramos-Pollán, Mauricio Toro
A two-stage data-driven metaheuristic to predict last-mile delivery route sequences. Eng. Appl. Artif. Intell. 125 (2023)
Fabio A. González, Raúl Ramos-Pollán, Joseph A. Gallego-Mejia
Quantum Kernel Mixtures for Probabilistic Deep Learning. CoRR (2023)
Raúl Ramos-Pollán, Fabio A. González
Lightweight learning from label proportions on satellite imagery. CoRR (2023)
Omar A. Castaño-Idarraga, Raúl Ramos-Pollán, Freddie Kalaitzis
A contrastive method based on elevation data for remote sensing with scarce and high level semantic labels. CoRR (2023)
Joseph A. Gallego-Mejia, Anna Jungbluth, Laura Martínez-Ferrer, Matt Allen, Francisco Dorr, Freddie Kalaitzis, Raúl Ramos-Pollán
Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery. CoRR (2023)
Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
SAR-based landslide classification pretraining leads to better segmentation. CoRR (2022)
Miguel Plazas, Raúl Ramos-Pollán, Fabian León, Fabio Martínez
Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy. Medical Imaging: Image Processing (2022)
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
Deep learning based landslide density estimation on SAR data for rapid response. CoRR (2022)
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. CoRR (2022)
Diego Rueda-Plata, Raúl Ramos-Pollán, Fabio A. González
Effective training of convolutional neural networks with small, specialized datasets. J. Intell. Fuzzy Syst. 32 (2) (2017)
John Edison Arevalo Ovalle, Fabio A. González, Raúl Ramos-Pollán, José Luís Oliveira, Miguel Ángel Guevara-López
Representation learning for mammography mass lesion classification with convolutional neural networks. Comput. Methods Programs Biomed. 127 (2016)
Susana Sanchez-Naranjo, Fabio A. González, Raúl Ramos-Pollán, Marc Solé
Data driven Vertical Total Electron Content workflow for GNSS positioning for single frequency receivers. ICL-GNSS (2016)
Dario Garcia-Gasulla, Jonathan Moreno, Raúl Ramos-Pollán, Romel Casadiegos Barrios, Javier Béjar, Ulises Cortés, Eduard Ayguadé, Jesús Labarta, Toyotaro Suzumura
On the Representativeness of Convolutional Neural Networks Layers. CCIA (2016)
Francy Camacho, Rodrigo Torres, Raúl Ramos-Pollán
Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides. CMSB (2015)
Diego Rueda-Plata, Raúl Ramos-Pollán, Fabio A. González
Supervised Greedy Layer-Wise Training for Deep Convolutional Networks with Small Datasets. ICCCI (1) (2015)
Sebastián Sierra, Juan F. Molina, Angel Cruz-Roa, José Daniel Pabón, Raúl Ramos-Pollán, Fabio A. González, Hugo Franco
Classification of Low-Level Atmospheric Structures Based on a Pyramid Representation and a Machine Learning Method. CIARP (2015)
John Edison Arevalo Ovalle, Fabio A. González, Raúl Ramos-Pollán, José Luís Oliveira, Miguel Ángel Guevara-López
Convolutional neural networks for mammography mass lesion classification. EMBC (2015)
John Edison Arevalo Ovalle, Raúl Ramos-Pollán, Fabio A. González
Distributed Cache Strategies for Machine Learning Classification Tasks over Cluster Computing Resources. CARLA (2014)
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
Benchmarking Datasets for Breast Cancer Computer-Aided Diagnosis (CADx). CIARP (1) (2013)
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
Exchanging Data for Breast Cancer Diagnosis on Heterogeneous Grid Platforms. Comput. Informatics 31 (1) (2012)
Raúl Ramos-Pollán, Miguel Ángel Guevara-López, Eugénio C. Oliveira
A Software Framework for Building Biomedical Machine Learning Classifiers through Grid Computing Resources. J. Medical Syst. 36 (4) (2012)
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
Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis. J. Medical Syst. 36 (4) (2012)
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
BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. eScience (2012)
Jorge A. Vanegas, Juan C. Caicedo, Jorge E. Camargo, Raúl Ramos-Pollán, Fabio A. González
Bioingenium at ImageCLEF 2012: Text and Visual Indexing for Medical Images. CLEF (Online Working Notes/Labs/Workshop) (2012)
Raúl Ramos-Pollán, Miguel Ángel Guevara-López, Eugénio C. Oliveira
Introducing ROC Curves as Error Measure Functions: A New Approach to Train ANN-Based Biomedical Data Classifiers. CIARP (2010)
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
CardioGRID: a framework for the analysis of cardiological signals in GRID computing. LANOMS (2009)