Raúl Ramos-Pollán

Orcid: 0000-0001-6195-3612

According to our database1, Raúl Ramos-Pollán authored at least 35 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:

On csauthors.net:


M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data.
CoRR, 2024

A Bi-Objective Approach to Last-Mile Delivery Routing Considering Driver Preferences.
CoRR, 2024

A two-stage data-driven metaheuristic to predict last-mile delivery route sequences.
Eng. Appl. Artif. Intell., 2023

Exploring DINO: Emergent Properties and Limitations for Synthetic Aperture Radar Imagery.
CoRR, 2023

Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction.
CoRR, 2023

Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data.
CoRR, 2023

Fewshot learning on global multimodal embeddings for earth observation tasks.
CoRR, 2023

Lightweight learning from label proportions on satellite imagery.
CoRR, 2023

Quantum Kernel Mixtures for Probabilistic Deep Learning.
CoRR, 2023

A Contrastive Method Based on Elevation Data for Remote Sensing with Scarce and High Level Semantic Labels.
CoRR, 2023

Deep learning based landslide density estimation on SAR data for rapid response.
CoRR, 2022

SAR-based landslide classification pretraining leads to better segmentation.
CoRR, 2022

Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes.
CoRR, 2022

Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy.
Proceedings of the Medical Imaging 2022: Image Processing, 2022

Sensitivity of deep learning applied to spatial image steganalysis.
PeerJ Comput. Sci., 2021

Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain.
PeerJ Comput. Sci., 2021

GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis.
IEEE Access, 2021

Deep Learning Applied to Steganalysis of Digital Images: A Systematic Review.
IEEE Access, 2019

Effective training of convolutional neural networks with small, specialized datasets.
J. Intell. Fuzzy Syst., 2017

Representation learning for mammography mass lesion classification with convolutional neural networks.
Comput. Methods Programs Biomed., 2016

Data driven Vertical Total Electron Content workflow for GNSS positioning for single frequency receivers.
Proceedings of the International Conference on Localization and GNSS, 2016

On the Representativeness of Convolutional Neural Networks Layers.
Proceedings of the Artificial Intelligence Research and Development, 2016

Supervised Greedy Layer-Wise Training for Deep Convolutional Networks with Small Datasets.
Proceedings of the Computational Collective Intelligence - 7th International Conference, 2015

Convolutional neural networks for mammography mass lesion classification.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides.
Proceedings of the Computational Methods in Systems Biology, 2015

Classification of Low-Level Atmospheric Structures Based on a Pyramid Representation and a Machine Learning Method.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015

Distributed Cache Strategies for Machine Learning Classification Tasks over Cluster Computing Resources.
Proceedings of the High Performance Computing - First HPCLATAM, 2014

Benchmarking Datasets for Breast Cancer Computer-Aided Diagnosis (CADx).
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013

Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis.
J. Medical Syst., 2012

A Software Framework for Building Biomedical Machine Learning Classifiers through Grid Computing Resources.
J. Medical Syst., 2012

Exchanging Data for Breast Cancer Diagnosis on Heterogeneous Grid Platforms.
Comput. Informatics, 2012

BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources.
Proceedings of the 8th IEEE International Conference on E-Science, 2012

Bioingenium at ImageCLEF 2012: Text and Visual Indexing for Medical Images.
Proceedings of the CLEF 2012 Evaluation Labs and Workshop, 2012

Introducing ROC Curves as Error Measure Functions: A New Approach to Train ANN-Based Biomedical Data Classifiers.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2010

CardioGRID: a framework for the analysis of cardiological signals in GRID computing.
Proceedings of the 2009 Latin American Network Operations and Management Symposium, 2009