Maximizing the Accuracy of Continuous Quantification Measures Using Discrete PackTest Products with Deep Learning and Pseudocolor Imaging
Author
Source
Journal of Analytical Methods in Chemistry
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-09
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Using the standard colors provided in the instructions, PackTest products can approximate and quickly estimate the chemical characteristics of liquid samples.
The combination of PackTest products and deep learning was examined for its accuracy and precision in quantifying chemical oxygen demand, ammonium ion, and phosphate ion using a pseudocolor imaging method.
Each PackTest product underwent reactions with standard solutions.
The generated color was scanner-read.
From the color image, ten grayscale images representing the intensity values of red, green, blue, cyan, magenta, yellow, key black, and L∗, and the values of a∗ and b∗ were generated.
Using the grayscale images representing the red, green, and blue intensity values, 73 other grayscale images were generated.
The grayscale intensity values were used to prepare datasets for the ten and 83 (=10 + 73) images.
For both datasets, chemical oxygen demand quantification was successful, resulting in values of normalized mean absolute error of less than 0.4% and coefficients of determination that were greater than 0.9996.
However, the quantification of ammonium and phosphate ions commonly provided false positive results for the standard solution that contained no ammonium ion/phosphate ion.
For ammonium ion, multiple regression markedly improved the accuracy using the pseudocolor method.
Phosphate ion quantification was also improved by avoiding the use of an estimated value for the reference solution that contained no phosphate ion.
Real details of the measurements and the perspectives were discussed.
American Psychological Association (APA)
Doi, Ryoichi. 2019. Maximizing the Accuracy of Continuous Quantification Measures Using Discrete PackTest Products with Deep Learning and Pseudocolor Imaging. Journal of Analytical Methods in Chemistry،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1169035
Modern Language Association (MLA)
Doi, Ryoichi. Maximizing the Accuracy of Continuous Quantification Measures Using Discrete PackTest Products with Deep Learning and Pseudocolor Imaging. Journal of Analytical Methods in Chemistry No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1169035
American Medical Association (AMA)
Doi, Ryoichi. Maximizing the Accuracy of Continuous Quantification Measures Using Discrete PackTest Products with Deep Learning and Pseudocolor Imaging. Journal of Analytical Methods in Chemistry. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1169035
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169035