Time–Frequency Transformations for Enhanced Biomedical Signal Classification with Convolutional Neural Networks

Time–Frequency Transformations for Enhanced Biomedical Signal Classification with Convolutional Neural Networks

<b>Background:</b> Transforming one-dimensional (1D) biomedical signals into two-dimensional (2D) images enables the application of convolutional neural networks (CNNs) for classification tasks. In this study, we investigated the effectiveness of different 1D-to-2D transformation methods...

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Bibliographic Details
Main Authors: Georgios Lekkas, Eleni Vrochidou, George A. Papakostas
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:BioMedInformatics
Subjects:
biomedical signal processing
AI in healthcare
biomedical AI
electrocardiogram (ECG) classification
ECGs
deep learning
Online Access:https://www.mdpi.com/2673-7426/5/1/7
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