Practical model for improved classification of trace chemical residues on surfaces in active spectroscopic measurements
Author:
Affiliation:
1. Systems and Technology Research, Woburn, Massachusetts
2. Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, Rochester, New Yor
3. Block MEMS, Southborough, Massachusetts
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Engineering,Atomic and Molecular Physics, and Optics
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Setup and Analysis of a Mid-Infrared Stand-Off System to Detect Traces of Explosives on Fabrics;Sensors;2022-10-15
2. Machine learning algorithms for identification of trace explosives by active infrared backscatter hyperspectral imaging;Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII;2022-05-31
3. Algorithms for identification of trace explosives by active infrared backscatter hyperspectral imaging;Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII;2021-04-12
4. Physics-guided neural network for predicting chemical signatures;Applied Optics;2021-04-07
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