:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Atienza, Adrian, Manimaran, Gouthamaan, Puthusserypady, Sadasivan, Dominguez, Helena, Jacobsen, Peter K., Bardram, Jakob E.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Signal Processing
Online Access:	https://arxiv.org/abs/2503.02621
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

NERULA: A Dual-Pathway Self-Supervised Learning Framework for Electrocardiogram Signal Analysis
by: Manimaran, Gouthamaan, et al.
Published: (2024)

CuPID: Leveraging Masked Single-Lead ECG Modelling for Enhancing the Representations
by: Atienza, Adtian, et al.
Published: (2025)

An Efficient and Flexible Deep Learning Method for Signal Delineation via Keypoints Estimation
by: Atienza, Adrian, et al.
Published: (2024)

Contrastive Learning Is Not Optimal for Quasiperiodic Time Series
by: Atienza, Adrian, et al.
Published: (2024)

Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
by: Atienza, Adtian, et al.
Published: (2025)

Applied Signal Processing
by: Puthusserypady, Sadasivan
Published: (2021)

IOT based Smart Helmet for Hazard Detection in mining industry
by: Kartik, B, et al.
Published: (2023)

Sampling Matters: The Effect of ECG Frequency on Deep Learning-Based Atrial Fibrillation Detection
by: Mahmuod, Arjan, et al.
Published: (2026)

Improving Multi‐Domain Autonomous Driving Data Classification Using Federated Learning‐Based Yolo With Adaptive Dilated Residual Attention Network
by: Manimaran Mannaperumal, et al.
Published: (2025)

A Deep Learning Method for Beat-Level Risk Analysis and Interpretation of Atrial Fibrillation Patients during Sinus Rhythm
by: Lei, Jun, et al.
Published: (2024)

Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
by: Jenkins, Alexander, et al.
Published: (2025)

RawECGNet: Deep Learning Generalization for Atrial Fibrillation Detection from the Raw ECG
by: Ben-Moshe, Noam, et al.
Published: (2023)

Feasibility Analysis of Federated Neural Networks for Explainable Detection of Atrial Fibrillation
by: Santos, Diogo Reis, et al.
Published: (2024)

Leveraging Non-Equilibrium ECRAM Dynamics for Short-Term Plasticity in Neuromorphic Circuits
by: Currie, Alex, et al.
Published: (2026)

Obstructive Sleep Apnea Characterization: A Multimodal Cross-Recurrence-Based Approach for Investigating Atrial Fibrillation
by: Rinkevičius, Mantas, et al.
Published: (2025)

Optimizing Medication Decisions for Patients with Atrial Fibrillation through Path Development Network
by: Xie, Tian
Published: (2024)

Leveraging Self-Supervised Learning for MIMO-OFDM Channel Representation and Generation
by: Liu, Zongxi, et al.
Published: (2024)

Remote Training in Task-Oriented Communication: Supervised or Self-Supervised with Fine-Tuning?
by: Li, Hongru, et al.
Published: (2025)

Using Test-Time Data Augmentation for Cross-Domain Atrial Fibrillation Detection from ECG Signals
by: Soleimani, Majid, et al.
Published: (2025)

Application of Joint Notch Filtering and Wavelet Transform for Enhanced Powerline Interference Removal in Atrial Fibrillation Electrograms
by: Martinez-Iniesta, Miguel, et al.
Published: (2024)

Low-power, Energy-efficient, Cardiologist-level Atrial Fibrillation Detection for Wearable Devices
by: Loroch, Dominik, et al.
Published: (2025)

Time Variability of FibrillatoryWaves Energy Predicts Long-Term Outcome of Atrial Fibrillation Concomitant Surgical Ablation
by: Rodenas, Juan, et al.
Published: (2024)

Preoperative Prediction of Catheter Ablation Outcome in Persistent Atrial Fibrillation Patients through Spectral Organization Analysis of the Surface Fibrillatory Waves
by: Escribano, P., et al.
Published: (2024)

Spectral Distribution Complexity of the Surface Fibrillatory Waves Predicts Post-Catheter Ablation Relapse in Persistent Atrial Fibrillation
by: Escribano, Pilar, et al.
Published: (2024)

Catheter Ablation Outcome Prediction With Advanced Time-Frequency Features of the Fibrillatory Waves From Patients in Persistent Atrial Fibrillation
by: Escribano, Pilar, et al.
Published: (2024)

Balloon Cryoablation for Paroxysmal Atrial Fibrillation. Initial Experience
by: JOSÉ L. GONZÁLEZ
Published: (2015)

Novel Entropy-Based Metrics for Long-Term Atrial Fibrillation Recurrence Prediction Following Surgical Ablation: Insights from Preoperative Electrocardiographic Analysis
by: Escribano, P., et al.
Published: (2024)

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
by: Kechris, Christodoulos, et al.
Published: (2024)

Cascaded Self-supervised Learning for Subject-independent EEG-based Emotion Recognition
by: Wang, Hanqi, et al.
Published: (2024)

Self-Supervised Learning for Covariance Estimation
by: Diskin, Tzvi, et al.
Published: (2024)

SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals
by: Yan, Runze, et al.
Published: (2024)

Leveraging Large Self-Supervised Time-Series Models for Transferable Diagnosis in Cross-Aircraft Type Bleed Air System
by: Wang, Yilin, et al.
Published: (2025)

A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection
by: Le, Thanh-Dung, et al.
Published: (2024)

Predictors of Recurrence and Outcomes in Catheter Ablation of Paroxysmal Atrial Fibrillation
by: LEANDRO TOMAS
Published: (2017)

Paroxysmal Atrial Fibrillation: Cryoballoon versus Radiofrequency Catheter Ablation
by: AGUSTÍN OROSCO
Published: (2017)

Emergency Department Serum Electrolyte Patterns in Paroxysmal Atrial Fibrillation
by: Zahra Hooshanginezhad, et al.
Published: (2025)

Self-Supervised Learning at the Edge: The Cost of Labeling
by: Pereira, Roberto, et al.
Published: (2025)

Semi-Supervised Dual-Stream Self-Attentive Adversarial Graph Contrastive Learning for Cross-Subject EEG-based Emotion Recognition
by: Ye, Weishan, et al.
Published: (2023)

SelfEEG: A Python library for Self-Supervised Learning in Electroencephalography
by: Del Pup, Federico, et al.
Published: (2023)

RAG-based EEG-to-Text Translation Using Deep Learning and LLMs
by: Collautti, Enrico, et al.
Published: (2026)