Cite
PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection.
MLA
Abir, Farhan Fuad, et al. “PCovNet+: A CNN-VAE Anomaly Detection Framework with LSTM Embeddings for Smartwatch-Based COVID-19 Detection.” Engineering Applications of Artificial Intelligence, vol. 122, June 2023, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.engappai.2023.106130.
APA
Abir, F. F., Chowdhury, M. E. H., Tapotee, M. I., Mushtak, A., Khandakar, A., Mahmud, S., & Hasan, A. (2023). PCovNet+: A CNN-VAE anomaly detection framework with LSTM embeddings for smartwatch-based COVID-19 detection. Engineering Applications of Artificial Intelligence, 122, N.PAG. https://doi.org/10.1016/j.engappai.2023.106130
Chicago
Abir, Farhan Fuad, Muhammad E.H. Chowdhury, Malisha Islam Tapotee, Adam Mushtak, Amith Khandakar, Sakib Mahmud, and Anwarul Hasan. 2023. “PCovNet+: A CNN-VAE Anomaly Detection Framework with LSTM Embeddings for Smartwatch-Based COVID-19 Detection.” Engineering Applications of Artificial Intelligence 122 (June): N.PAG. doi:10.1016/j.engappai.2023.106130.