Predicting Response of Printed Potentiometric Nitrate Sensors Using Image Based Machine Learning

Qingyu Yang; Kerry Maize; Xin Jin; Hongjie Jiang; Md Ashraful Alam; Rahim Rahimi; George T.‐C. Chiu; Ali Shakouri; Jan P. Allebach

doi:10.2352/issn.2169-4451.2020.36.108

JOURNAL ARTICLE

Predicting Response of Printed Potentiometric Nitrate Sensors Using Image Based Machine Learning

Qingyu Yang Kerry Maize Xin Jin Hongjie Jiang Md Ashraful Alam Rahim Rahimi George T.‐C. Chiu Ali Shakouri Jan P. Allebach

Year: 2020 Journal: Technical programs and proceedings/Technical program and proceedings Vol: 36 (1)Pages: 108-113

DOI: 10.2352/issn.2169-4451.2020.36.108

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Keywords:

Potentiometric titration Nitrate Image (mathematics) Computer science Artificial intelligence Pattern recognition (psychology) Materials science Chemistry Electrode

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Advanced Chemical Sensor Technologies

Physical Sciences → Engineering → Biomedical Engineering

Analytical Chemistry and Sensors

Physical Sciences → Chemical Engineering → Bioengineering

Water Quality Monitoring and Analysis

Physical Sciences → Environmental Science → Industrial and Manufacturing Engineering

Predicting Response of Printed Potentiometric Nitrate Sensors Using Image Based Machine Learning

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