☆ 4.6 Article

Unsupervised Phonocardiogram Analysis With Distribution Density Based Variational Auto-Encoders

FRONTIERS IN MEDICINE (2021)

UNSUPERVISED HEART ABNORMALITY DETECTION BASED ON PHONOCARDIOGRAM ANALYSIS WITH BETA VARIATIONAL AUTO-ENCODERS

Shengchen Li et al.

Summary: This paper proposes an unsupervised PCG analysis method using beta-VAE to model normal PCG signals, achieving a good performance. The study suggests that anomaly scores based on reconstruction loss may be better than those based on latent vectors.

2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021) (2021)

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Proceedings Paper Acoustics

A SEMI-SUPERVISED APPROACH FOR IDENTIFYING ABNORMAL HEART SOUNDS USING VARIATIONAL AUTOENCODER

Rohan Banerjee et al.

2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (2020)

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Proceedings Paper Acoustics

ToyADMOS: A DATASET OF MINIATURE-MACHINE OPERATING SOUNDS FOR ANOMALOUS SOUND DETECTION

Yuma Koizumi et al.

2019 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) (2019)

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Article Engineering, Electrical & Electronic

Statistical feature embedding for heart sound classification

Mohammad Adiban et al.

JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS (2019)

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Article Biophysics

An open access database for the evaluation of heart sound algorithms

Chengyu Liu et al.

PHYSIOLOGICAL MEASUREMENT (2016)

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Unsupervised Phonocardiogram Analysis With Distribution Density Based Variational Auto-Encoders

相关参考文献

UNSUPERVISED HEART ABNORMALITY DETECTION BASED ON PHONOCARDIOGRAM ANALYSIS WITH BETA VARIATIONAL AUTO-ENCODERS

A SEMI-SUPERVISED APPROACH FOR IDENTIFYING ABNORMAL HEART SOUNDS USING VARIATIONAL AUTOENCODER

ToyADMOS: A DATASET OF MINIATURE-MACHINE OPERATING SOUNDS FOR ANOMALOUS SOUND DETECTION

Statistical feature embedding for heart sound classification

An open access database for the evaluation of heart sound algorithms

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