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Multiscale Convolution and Attention based Denoising Autoencoder for Motion Artifact Removal in ECG Signals.

, , , , , , and . ICIGP, page 442-448. ACM, (2024)

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Diagnosis of atrial fibrillation based on lightweight detail-semantic network., , , , and . Biomed. Signal Process. Control., (August 2023)Robust Feature Selection Based on Fuzzy Rough Sets with Representative Sample., , , , , , and . ADMA, volume 11888 of Lecture Notes in Computer Science, page 151-165. Springer, (2019)Deep learning-based context aggregation network for tumor diagnosis., , and . CISP-BMEI, page 1-6. IEEE, (2021)Coupling Analysis for Systolic, Diastolic and RR Interval Time Series Using Multivariable Fuzzy Measure Entropy., , , and . CinC, www.cinc.org, (2017)Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality., , , and . J. Electr. Comput. Eng., (2015)Multiscale Convolution and Attention based Denoising Autoencoder for Motion Artifact Removal in ECG Signals., , , , , , and . ICIGP, page 442-448. ACM, (2024)An atrial fibrillation detection algorithm based on lightweight design architecture and feature fusion strategy., , , , , , and . Biomed. Signal Process. Control., (2024)Predicting spontaneous termination of atrial fibrillation based on dual path network and feature selection., , , , , , and . Biomed. Signal Process. Control., 88 (Part B): 105606 (February 2024)Comparison of Four Recovery Algorithms Used in Compressed Sensing for ECG Signal Processing., , , , , and . CinC, www.cinc.org, (2016)Detection of AF and I-AVB combined with RR interval and P wave., , , , , , and . CISP-BMEI, page 834-839. IEEE, (2020)