2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) 2017
DOI: 10.1109/nssmic.2017.8533106
|View full text |Cite
|
Sign up to set email alerts
|

Application of Multivariate Data Analysis Techniques for the Portable Isotopic Neutron Spectroscopy System

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
1
0

Year Published

2019
2019
2019
2019

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 7 publications
0
1
0
Order By: Relevance
“…INL has a collection of gamma-ray spectra of various chemical-fills from the field-deployed PINS systems over the years, and it was envisaged to leverage such valuable resources with other classification methods. An algorithm based on the Principal Components Analysis (PCA) technique has shown possibility of unsupervised learning[3]. As part of an ongoing research effort to improve the PINS identification algorithm, an Artificial Neural Network (ANN) algorithm was developed to identify CWA.…”
mentioning
confidence: 99%
“…INL has a collection of gamma-ray spectra of various chemical-fills from the field-deployed PINS systems over the years, and it was envisaged to leverage such valuable resources with other classification methods. An algorithm based on the Principal Components Analysis (PCA) technique has shown possibility of unsupervised learning[3]. As part of an ongoing research effort to improve the PINS identification algorithm, an Artificial Neural Network (ANN) algorithm was developed to identify CWA.…”
mentioning
confidence: 99%