Methods › Sequential › Time Series Analysis › CNN-TS
A Deep Convolutional Neural Network for Time Series Classification with Intermediate Targets
CNN-TS
Introduced by Aboozar Taherkhani et al. in A Deep Convolutional Neural Network for Time Series Classification with Intermediate Targets
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
CNN-TS: A Deep Convolutional Neural Network for Time Series Classification
This method leverages deep convolutional neural networks to classify time series data with intermediate targets. It is designed to improve accuracy in time series analysis.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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A Deep Convolutional Neural Network for Time Series Classification with Intermediate Targets 28 Oct 2023 · 1 repository
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Time Series | 1 |
| Time Series Classification | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections