Jul 6, 2022 · In this article, several models have been presented that use temporal discretization as a step of preprocessing time series and embed it in the deep neural ...
Jul 4, 2022 · Abstract—Deep learning-based time series classification techniques have significantly improved in recent years.
DTGNN [2] is designed to specifically handle time series data, it might offer advantages in capturing temporal dependencies and dynamics in the data, which is ...
A Novel Embedded Discretization-Based Deep Learning Architecture for Multivariate Time Series Classification. M. Tahan, M. Ghasemzadeh, and S. Asadi.
Co-authors ; A Novel Embedded Discretization-Based Deep Learning Architecture for Multivariate Time Series Classification. MH Tahan, M Ghasemzadeh, S Asadi. IEEE ...
This paper seeks to introduce a novel deep learning-based Optimal Dynamic Time Warping (ODTW) paradigm for multimodal time's series data categorization.
A novel embedded discretization-based deep learning architecture for multivariate time series classification. MH Tahan, M Ghasemzadeh, S Asadi. IEEE ...
M. H. Tahan, M. Ghasemzadeh and S. Asadi, "A Novel Embedded Discretization-Based. Deep Learning Architecture for Multivariate Time Series Classification," IEEE.
People also ask
What is the best architecture for time series classification?
A Novel Embedded Discretization-Based Deep Learning Architecture for Multivariate Time Series Classification · Computer Science. IEEE Transactions on Industrial ...
This paper surveys the current state of the art in the fast-moving field of deep learning for time series classification and extrinsic regression. We review ...
Missing: Discretization- | Show results with:Discretization-