Imagen de Portada

Investigating the Generalizability of ECG Noise Detection Across Diverse Data Sources and Noise Types

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kalpande, Sharmad, Sahu, Nilesh Kumar, Lone, Haroon
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Evaluating Federated Learning for Cross-Country Mood Inference from Smartphone Sensing Data
por: Kalpande, Sharmad, et al.
Publicado: (2026)

Are Anxiety Detection Models Generalizable? A Cross-Activity and Cross-Population Study Using Wearables
por: Sahu, Nilesh Kumar, et al.
Publicado: (2025)

AnxietyFaceTrack: A Smartphone-Based Non-Intrusive Approach for Detecting Social Anxiety Using Facial Features
por: Sahu, Nilesh Kumar, et al.
Publicado: (2025)

HCFSLN: Adaptive Hyperbolic Few-Shot Learning for Multimodal Anxiety Detection
por: Sneh, Aditya, et al.
Publicado: (2025)

DySTAN: Joint Modeling of Sedentary Activity and Social Context from Smartphone Sensors
por: Sneh, Aditya, et al.
Publicado: (2025)

Harnessing Smartwatch Microphone Sensors for Cough Detection and Classification
por: Jaiswal, Pranay, et al.
Publicado: (2024)

Exploring Heart Rate Variability and Heart Rate Dynamics Using Wearables Before, During, and After Speech Activity: Insights from a Controlled Study in a Low-Middle-Income Country
por: Sahu, Nilesh Kumar, et al.
Publicado: (2025)

FedPrism: Adaptive Personalized Federated Learning under Non-IID Data
por: Kumbhakar, Prakash, et al.
Publicado: (2026)

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning
por: Waykole, Vedant, et al.
Publicado: (2026)

DECODE: Data-driven Energy Consumption Prediction leveraging Historical Data and Environmental Factors in Buildings
por: Mishra, Aditya, et al.
Publicado: (2023)

RiM: Record, Improve and Maintain Physical Well-being using Federated Learning
por: Mishra, Aditya, et al.
Publicado: (2025)

Exploring Social Media Posts for Depression Identification: A Study on Reddit Dataset
por: Harshit, Nandigramam Sai, et al.
Publicado: (2024)

Beyond Questionnaires: Video Analysis for Social Anxiety Detection
por: Sahu, Nilesh Kumar, et al.
Publicado: (2024)

Thermal Vision: Pioneering Non-Invasive Temperature Tracking in Congested Spaces
por: Samal, Arijit, et al.
Publicado: (2024)

An Offline Mobile Conversational Agent for Mental Health Support: Learning from Emotional Dialogues and Psychological Texts with Student-Centered Evaluation
por: A, Vimaleswar, et al.
Publicado: (2025)

Real-World Receptivity to Adaptive Mental Health Interventions: Findings from an In-the-Wild Study
por: Sahu, Nilesh Kumar, et al.
Publicado: (2025)

On the Generalizability of ECG-based Stress Detection Models
por: Prajod, Pooja, et al.
Publicado: (2022)

Fairness-Aware Few-Shot Learning for Audio-Visual Stress Detection
por: Shelke, Anushka Sanjay, et al.
Publicado: (2025)

CA-AFP: Cluster-Aware Adaptive Federated Pruning
por: Jha, Om Govind, et al.
Publicado: (2026)

DohaScript: A Large-Scale Multi-Writer Dataset for Continuous Handwritten Hindi Text
por: Singh, Kunwar Arpit, et al.
Publicado: (2026)

EDN: A Novel Edge-Dependent Noise Model for Graph Data
por: Kumar, Pintu, et al.
Publicado: (2025)

NoiseFormer -- Noise Diffused Symmetric Attention Transformer
por: Kumar, Phani, et al.
Publicado: (2026)

Leveraging language models for summarizing mental state examinations: A comprehensive evaluation and dataset release
por: Sahu, Nilesh Kumar, et al.
Publicado: (2024)

Noise2Noise Denoising of CRISM Hyperspectral Data
por: Platt, Robert, et al.
Publicado: (2024)

Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation
por: Dai, Wei, et al.
Publicado: (2024)

Detecting Adversarial Data via Provable Adversarial Noise Amplification
por: Mumcu, Furkan, et al.
Publicado: (2026)

Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise
por: Meng, Li, et al.
Publicado: (2022)

Mitigating Label Noise through Data Ambiguation
por: Lienen, Julian, et al.
Publicado: (2023)

Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
por: Xue, Yihao, et al.
Publicado: (2022)

Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
por: Shubham, Kumar, et al.
Publicado: (2026)

Spectral Edge Dynamics of Training Trajectories: Signal--Noise Geometry Across Scales
por: Xu, Yongzhong
Publicado: (2026)

Rectified Noise: A Generative Model Using Positive-incentive Noise
por: Gu, Zhenyu, et al.
Publicado: (2025)

Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
por: Yao, Yuan, et al.
Publicado: (2026)

DeGLIF for Label Noise Robust Node Classification using GNNs
por: Kumar, Pintu, et al.
Publicado: (2025)

Alternators With Noise Models
por: Rezaei, Mohammad R., et al.
Publicado: (2025)

Noise Robust One-Class Intrusion Detection on Dynamic Graphs
por: Liuliakov, Aleksei, et al.
Publicado: (2025)

Noise-contrastive Online Change Point Detection
por: Puchkin, Nikita, et al.
Publicado: (2022)

Mitigating the Noise Shift for Denoising Generative Models via Noise Awareness Guidance
por: Zhong, Jincheng, et al.
Publicado: (2025)

Early Stopping Against Label Noise Without Validation Data
por: Yuan, Suqin, et al.
Publicado: (2025)

Robust VAEs via Generating Process of Noise Augmented Data
por: Irobe, Hiroo, et al.
Publicado: (2024)