Skip to content
Log in
Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

D. Cárdenas-Peña

h-index 2 View on Semantic Scholar

We have 5 of 19 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Oct 2026

Physical Modeling and Optimal Sizing of Photovoltaic Generation Systems for Estimating Firm Energy Under Colombia’s Reliability Charge (ENFICC)

Photovoltaic (PV) plants participating in reliability mechanisms require design methods that assess both energy production and performance under critical resource conditions. This paper presents a computational methodology for physical modeling and optimal sizing of grid-connected PV systems to estimate Firm Energy und...

Sebastián Orozco-Bañol, A. Escobar-Mejía, D. Cárdenas-Peña · 0 citations
Open access Aug 2026

PPG-FusionNet: A Dual-Branch Neural Architecture for Cuffless Blood Pressure Estimation from Photoplethysmography

Hypertension is a major risk factor for cardiovascular disease, yet cuffless blood pressure monitoring remains challenging because most existing methods rely on intermittent cuff-based measurements or multimodal physiological signals. This work proposes PPG-FusionNet, a dual-branch deep learning architecture for simult...

Eduardo Martínez-Duque, G. Daza-Santacoloma, D. Cárdenas-Peña · 0 citations
Open access Sep 2026

Transformer-Based Modeling of Directed Transfer Entropy Connectivity for EEG-Based ADHD Classification in Children

The Contextualized Transfer Entropy Network (CTE-Net) is proposed, an end-to-end deep-learning architecture that combines global content-based contextualization with nonlinear and directed EEG connectivity estimation and exhibited the lowest within-subject dispersion among the analyzed representation stages.

Alejandra Gomez-Rivera, J. D. Pastrana-Cortés, A. Álvarez-Meza et al. · 0 citations
Open access Jul 2026

EEG-Based Supported Diagnosis of ADHD Using Subject-Specific HMMs and Stationary RKHS Embeddings

This work introduces Hidden Markov Model-Induced Stationary RKHS Distance Learning (HIS), a probabilistic framework that represents each subject by a Hidden Markov Model with Gaussian-mixture emissions trained directly from frontal EEG recordings.

Leonardo Lopez-Ortiz, Cristhian K. Valencia-Marin, J. Gil-González et al. · 0 citations
Review Open access Jul 2026

Alignment-Aware 3D Point Cloud Anomaly Detection with Adversarial Normalizing Flows

An unsupervised framework that formulates 3D anomaly detection as a two-stage factorization problem, termed AdvFlow3D-AD, and an exploratory neurodevelopmental brain-shape case study involving pediatric perinatal-asphyxia cases suggest that separating geometric nuisance variation from residual morphology can support in...

A. Jiménez-García, Jonnatan Arias-Garcia, H. García et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.