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 signals. This paper presents a novel approach for heart sound segmentation and classification into S1 (LUB) and S2 (DUB) sounds. We employ FFT-based filtering%2C dynamic programming for event detection%2C and a Siamese network for robust classification. Our method demonstrates superior performance on the PASCAL heart sound dataset compared to existing approaches.?quality=80&w=800)
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- Heart Sound Segmentation using Switching Linear Dynamical Models | SigPort
- (PDF) HEART SOUND SEGMENTATION USING SWITCHING LINEAR DYNAMICAL MODELS
- (PDF) Heart sound segmentation using switching linear dynamical models
- Heart Sound Segmentation Using Deep Learning Techniques | AI Research Paper Details
- Heart Sound Segmentation Using Deep Learning Techniques | AI Research Paper Details
- Figure 2 from Heart sound segmentation using switching linear dynamical models | Semantic Scholar
- Figure 2 from Heart sound segmentation using switching linear dynamical models | Semantic Scholar
- Figure 2 from Heart sound segmentation using switching linear dynamical models | Semantic Scholar
- springer_heart_sound_segmentation_algorithm/models/segmentation_algorithm.py at master ...
- GitHub - MLtoPWELC/Heart-Sound-Segmentation: Temporal Convolutional Network Connected with an ...