March 28, 2024, 4:41 a.m. | Daniel Klenkert, Daniel Schaeffer, Julian Stauch

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.18687v1 Announce Type: new
Abstract: 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 %.

abstract arxiv classification comparison cs.lg data generated images implementation network networks neural networks series time series transformation type wavelet

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