A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry

A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry

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 possibi...

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Bibliographic Details
Main Authors: Mario Molinara, Rocco Cancelliere, Alessio Di Tinno, Luigi Ferrigno, Mikhail Shuba, Polina Kuzhir, Antonio Maffucci, Laura Micheli
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Sensors
Subjects:
carbon nanotubes
convolutional neural networks
pollutant detection
screen-printed electrodes
cyclic voltammetry
Online Access:https://www.mdpi.com/1424-8220/22/20/8032

Internet

https://www.mdpi.com/1424-8220/22/20/8032

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