A Deep Ensemble Model with an Efficient Feature for Multi-class Arrhythmia Classification Utilizing 12-Lead ECG Signal

MLA

Md. Sultan Mahmud, et al. “A Deep Ensemble Model with an Efficient Feature for Multi-Class Arrhythmia Classification Utilizing 12-Lead ECG Signal.” 2022 12th International Conference on Electrical and Computer Engineering (ICECE), Dec. 2022. EBSCOhost, https://doi.org/10.1109/icece57408.2022.10088465.

APA

Md. Sultan Mahmud, Md. Mizanur Rahaman Nayan, Samit Hasan, & Md. Nasim Afroj Taj. (2022). A Deep Ensemble Model with an Efficient Feature for Multi-class Arrhythmia Classification Utilizing 12-Lead ECG Signal. 2022 12th International Conference on Electrical and Computer Engineering (ICECE). https://doi.org/10.1109/icece57408.2022.10088465

Chicago

Md. Sultan Mahmud, Md. Mizanur Rahaman Nayan, Samit Hasan, and Md. Nasim Afroj Taj. 2022. “A Deep Ensemble Model with an Efficient Feature for Multi-Class Arrhythmia Classification Utilizing 12-Lead ECG Signal.” 2022 12th International Conference on Electrical and Computer Engineering (ICECE), December. doi:10.1109/icece57408.2022.10088465.