Cite
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study)
MLA
Aguilera-Martos, Ignacio, et al. TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction Using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study). 2022. EBSCOhost, widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.2206.03179&authtype=sso&custid=ns315887.
APA
Aguilera-Martos, I., García-Vico, Á. M., Luengo, J., Damas, S., Melero, F. J., Valle-Alonso, J. J., & Herrera, F. (2022). TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).
Chicago
Aguilera-Martos, Ignacio, Ángel M. García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, and Francisco Herrera. 2022. “TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction Using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).” http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.2206.03179&authtype=sso&custid=ns315887.