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InceptionTime vs. Wavelet -- A comparison for time series classification

arXiv 2403.18687 ↗First posted 27 Mar 2024cs.LGcited by 0

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Abstract (arXiv)

Neural networks were used to classify infrasound data. Two different approaches were compared. One based on the direct classification of time series data, using a custom implementation of the InceptionTime network. For the other approach, we generated 2D images of the wavelet transformation of the signals, which were subsequently classified using a ResNet implementation. Choosing appropriate hyperparameter settings, both achieve a classification accuracy of above 90 %, with the direct approach reaching 95.2 %.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 6 references that are in the map. First posted on arXiv 27 Mar 2024.

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References · 3

  1. 2019InceptionTime: Finding AlexNet for Time Series Classificationcited by 387
  2. 2020MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classificationcited by 190
  3. 2020fastai: A Layered API for Deep Learningcited by 183

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