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GitHub / foryichuanqi / TKDE-Paper-2023.10-Time-series-classification-by-MEB-ResNet

Paper: Multi-Scale Ensemble Booster for Improving Existing TSD Classifiers. We proposed a highly easy-to-use performance enhancement framework called multi-scale ensemble booster(MEB), helping existing time series classification methods achieve performance leap. Our proposed MEB-ResNet achieved the most advanced time series classification ability.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/foryichuanqi%2FTKDE-Paper-2023.10-Time-series-classification-by-MEB-ResNet

Stars: 4
Forks: 0
Open Issues: 0

License: None
Language: Python
Repo Size: 1.62 MB
Dependencies: 0

Created: over 1 year ago
Updated: about 2 months ago
Last pushed: about 1 year ago
Last synced: about 2 months ago

Topics: deep-learning, ensemble, multi-scale, multivariate-time-series, time-series-classification, ucr-repository, unvariate-time-series

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