In this work, we present the development, description, and performance evaluation of two
volcano seismological datasets: one containing raw seismic signals (MicSigV1) and another …

Microseismic monitoring systems deployed in deep underground engineering can capture
massive waveform signals in real time. However, some noise signals are highly deceptive …

This paper explores the use of six different clustering-based methods to classify long-period
and volcano-tectonic seismic events and to find possible overlap** signals of non …

This article proposes a new volcano seismic signal descriptor for improving the area under
the receiver operating characteristic curve (AUC) in the classification of long-period (LP) and …

The identification of suspicious microseismic events is the first crucial step in processing
microseismic data. In this paper, we present an automatic classification method based on a …

There is a lot of redundancy in the high dimensional raw images, which not only greatly
increases the computational burden of image classification process, but also inevitably …

With the growing ability to collect large volumes of volcano seismic data, the detection and
labeling process of these records is increasingly challenging. Clearly, analyzing all …

Acquisition, classification, and analysis of seismic data are crucial tasks in volcano
monitoring. The large number of seismic signals that are continuously acquired during the …

The proper identification of several types of volcanic seismic events can be related to the
intrinsic behavior of a volcano, and it could be useful to provide an early alarm in the case of …

Purpose The COVID-19 pandemic situation is increasing day by day and has affected the
lifestyle and economy worldwide. Due to the absence of specific treatment, the only way to …