Suchergebnisse - "discriminative convolutional sparse coding"

Discriminative Convolutional Sparse Coding of ECG Signals for Automated Recognition of Cardiac Arrhythmias

Autoren: Bing Zhang Jizhong Liu

Quelle: Mathematics, Vol 10, Iss 16, p 2874 (2022)

Schlagwörter: electrocardiogram signal, discriminative convolutional sparse coding, dictionary filter learning, linear SVM, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2227-7390/10/16/2874; https://doaj.org/toc/2227-7390

Zugangs-URL: https://doaj.org/article/608f4e93e2a94437a14964b187671cb7

Discriminative Convolutional Sparse Coding of ECG Signals for Automated Recognition of Cardiac Arrhythmias.

Autoren: Zhang, Bing Liu, Jizhong

Quelle: Mathematics (2227-7390); Aug2022, Vol. 10 Issue 16, p2874-2874, 20p

Schlagwörter: ARRHYTHMIA, SUPPORT vector machines, ELECTROCARDIOGRAPHY, COMPUTATIONAL complexity

Incorporation of Histogram Intersection and Semantic Information into Non-Negative Local Laplacian Sparse Coding for Image Classification.

Autoren: Shi, Ying Wan, Yuan Wang, Xinjian et al.

Quelle: Mathematics (2227-7390); Jan2025, Vol. 13 Issue 2, p219, 23p

Schlagwörter: IMAGE recognition (Computer vision), SUPPORT vector machines, ALGORITHMS, HISTOGRAMS, IMAGE representation

Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education.

Autoren: Lacave, Carmen Molina, Ana Isabel

Quelle: Mathematics (2227-7390); Mar2023, Vol. 11 Issue 6, p1344, 4p

Schlagwörter: ARTIFICIAL intelligence, INTELLIGENT tutoring systems, DEEP learning, ARTIFICIAL neural networks, MACHINE learning, CONVOLUTIONAL neural networks, NATURAL language processing

Classifying Cardiac Arrhythmia from ECG Signal Using 1D CNN Deep Learning Model.

Autoren: Ahmed, Adel A. Ali, Waleed Abdullah, Talal A. A. et al.

Quelle: Mathematics (2227-7390); Feb2023, Vol. 11 Issue 3, p562, 16p

Schlagwörter: ARRHYTHMIA, DEEP learning, BLOOD circulation, CONVOLUTIONAL neural networks, ELECTROCARDIOGRAPHY, AUTOMATIC classification