--- tags: - time series - time series classification - monster - other - seismic pretty_name: LenDB size_categories: - 1M. |LenDB|| |-|-:| |Category|Seismic| |Num. Examples|1,244,942| |Num. Channels|3| |Length|540| |Sampling Freq.|20 Hz| |Num. Classes|2| |License|[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)| |Citations|[1] [2]| ***LenDB*** consists of seismograms recorded from multiple different seismic detection networks from across the globe [1, 2]. The sampling rate is 20 Hz. The processed dataset consists of 1,244,942 multivariate time series, with 3 channels, each of length 540 (i.e., just under 30 seconds of data per time series at a sampling rate of 20 Hz), with two classes: earthquake and noise. This version of the dataset has been split into cross-validation folds based on seismic detection network (i.e., such that seismograms for a given network do not appear in both a training and validation fold). [1] Fabrizio Magrini, Dario Jozinovic, Fabio Cammarano, Alberto Michelini, and Lapo Boschi. (2020). Local earthquakes detection: A benchmark dataset of 3-component seismograms built on a global scale. *Artificial Intelligence in Geosciences*, 1:1–10. [2] Fabrizio Magrini, Dario Jozinovic, Fabio Cammarano, Alberto Michelini, and Lapo Boschi. (2020). LEN-DB Local earthquakes detection: A benchmark dataset of 3-component seismograms built on a global scale. . CC BY 4.0.