{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T10:54:58Z","timestamp":1777028098898,"version":"3.51.4"},"reference-count":41,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000830","name":"NATO","doi-asserted-by":"publisher","award":["G5777"],"award-info":[{"award-number":["G5777"]}],"id":[{"id":"10.13039\/501100000830","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000830","name":"NATO","doi-asserted-by":"publisher","award":["823878"],"award-info":[{"award-number":["823878"]}],"id":[{"id":"10.13039\/501100000830","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000830","name":"NATO","doi-asserted-by":"publisher","award":["320166"],"award-info":[{"award-number":["320166"]}],"id":[{"id":"10.13039\/501100000830","id-type":"DOI","asserted-by":"publisher"}]},{"name":"EU","award":["G5777"],"award-info":[{"award-number":["G5777"]}]},{"name":"EU","award":["823878"],"award-info":[{"award-number":["823878"]}]},{"name":"EU","award":["320166"],"award-info":[{"award-number":["320166"]}]},{"name":"Academy of Finland","award":["G5777"],"award-info":[{"award-number":["G5777"]}]},{"name":"Academy of Finland","award":["823878"],"award-info":[{"award-number":["823878"]}]},{"name":"Academy of Finland","award":["320166"],"award-info":[{"award-number":["320166"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper proposes a deep leaning technique for accurate detection and reliable classification of organic pollutants in water. The pollutants are detected by means of cyclic voltammetry characterizations made by using low-cost disposable screen-printed electrodes. The paper demonstrates the possibility of strongly improving the detection of such platforms by modifying them with nanomaterials. The classification is addressed by using a deep learning approach with convolutional neural networks. To this end, the results of the voltammetry analysis are transformed into equivalent RGB images by means of Gramian angular field transformations. The proposed technique is applied to the detection and classification of hydroquinone and benzoquinone, which are particularly challenging since these two pollutants have a similar electroactivity and thus the voltammetry curves exhibit overlapping peaks. The modification of electrodes by carbon nanotubes improves the sensitivity of a factor of about \u00d725, whereas the convolution neural network after Gramian transformation correctly classifies 100% of the experiments.<\/jats:p>","DOI":"10.3390\/s22208032","type":"journal-article","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:34:30Z","timestamp":1666312470000},"page":"8032","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6144-0654","authenticated-orcid":false,"given":"Mario","family":"Molinara","sequence":"first","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3278-0414","authenticated-orcid":false,"given":"Rocco","family":"Cancelliere","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technologies, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessio","family":"Di Tinno","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technologies, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1724-5720","authenticated-orcid":false,"given":"Luigi","family":"Ferrigno","sequence":"additional","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mikhail","family":"Shuba","sequence":"additional","affiliation":[{"name":"Center of Physical Science and Technologies, 10257 Vilnius, Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3689-0837","authenticated-orcid":false,"given":"Polina","family":"Kuzhir","sequence":"additional","affiliation":[{"name":"Institute of Photonics, Department of Physics and Mathematics, University of Eastern Finland, 80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4992-9449","authenticated-orcid":false,"given":"Antonio","family":"Maffucci","sequence":"additional","affiliation":[{"name":"Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy"},{"name":"INFN, Italian National Institute for Nuclear Physics, 00044 Frascati, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6970-0318","authenticated-orcid":false,"given":"Laura","family":"Micheli","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technologies, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"939","DOI":"10.2174\/1385272822666180404144834","article-title":"A Comprehensive Review of Analytical Methods for Determining Persistent Organic Pollutants in Air, Soil, Water and Waste","volume":"22","author":"Avino","year":"2018","journal-title":"Curr. 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