Methods › Sequential › Time Series Analysis › CNN-TS

A Deep Convolutional Neural Network for Time Series Classification with Intermediate Targets

CNN-TS

1 paper tagged archive 2025-07-28

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.

PaperSource

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.

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.

TaskPapers
Time Series1
Time Series Classification1

Usage over time archive 2025-07-28

Papers per year tagged with CNN-TS: 2023 to 2023, peak 1 1 0 2023: 1 paper 2023
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

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

Time Series Analysis

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