{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:45:19Z","timestamp":1760060719104,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"INGV internal project, ALISEI (Use of ArtificiaL Intelligence to improve SEIeismic data quality)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>SeismicNoiseAnalyzer 1.0 is a software tool designed to automatically assess the quality of seismic stations through the classification of spectral diagrams. By leveraging convolutional neural networks trained on expert-labeled data, the software emulates human visual inspection of probability density function (PDF) plots. It supports both individual image analysis and batch processing from compressed archives, providing detailed reports that summarize station health. Two classification networks are available: a binary model that distinguishes between working and malfunctioning stations and a ternary model that introduces an intermediate \u201cdoubtful\u201d category to capture ambiguous cases. The system demonstrates high agreement with expert evaluations and enables efficient instrumentation control across large seismic networks. Its intuitive graphical interface and automated workflow make it a valuable tool for routine monitoring and data validation.<\/jats:p>","DOI":"10.3390\/computers14090392","type":"journal-article","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T07:33:02Z","timestamp":1758007982000},"page":"392","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SeismicNoiseAnalyzer: A Deep-Learning Tool for Automatic Quality Control of Seismic Stations"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3172-2044","authenticated-orcid":false,"given":"Alessandro","family":"Pignatelli","sequence":"first","affiliation":[{"name":"Istituto Nazionale di Geofisica e Vulcanologia, 00143 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8656-7467","authenticated-orcid":false,"given":"Paolo","family":"Casale","sequence":"additional","affiliation":[{"name":"Istituto Nazionale di Geofisica e Vulcanologia, 00143 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5134-7282","authenticated-orcid":false,"given":"Veronica","family":"Vignoli","sequence":"additional","affiliation":[{"name":"Istituto Nazionale di Geofisica e Vulcanologia, 00143 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0315-9399","authenticated-orcid":false,"given":"Flavia","family":"Tavani","sequence":"additional","affiliation":[{"name":"Istituto Nazionale di Geofisica e Vulcanologia, 00143 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Peterson, J. 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