scholarly journals Temperature Profile Retrieval in Axisymmetric Combustion Plumes Using Multilayer Perceptron Modeling and Spectral Feature Selection in the Infrared CO2 Emission Band

2014 ◽  
Vol 68 (8) ◽  
pp. 900-908 ◽  
Author(s):  
Esteban García-Cuesta ◽  
Antonio J. de Castro ◽  
Inés M. Galván ◽  
Fernando López
Keyword(s):  
Feature Selection ◽  
Temperature Profile ◽  
Multilayer Perceptron ◽  
Emission Band ◽  
Co2 Emission ◽  
Spectral Feature ◽  
Spectral Feature Selection

LIBS development methodology for forensic nuclear materials analysis

2018 ◽  
Vol 10 (7) ◽  
pp. 791-798 ◽  
Author(s):  
Bobby Bhatt ◽  
Kalambuka Hudson Angeyo ◽  
Alix Dehayem-Kamadjeu
Keyword(s):  
Feature Selection ◽  
Spectral Feature ◽  
Forensic Analysis ◽  
Nuclear Materials ◽  
Methodology Development ◽  
Materials Analysis ◽  
Development Methodology ◽  
Selection For ◽  
Spectral Feature Selection ◽  
Nuclear Forensic

Methodology development of LIBS coupled with chemometrics utilizing weak U-lines and spectral feature selection for rapid nuclear forensic analysis.

Genetic algorithm spectral feature selection coupled with quadratic discriminant analysis for ATR-FTIR spectrometric diagnosis of basal cell carcinoma via blood sample analysis

RSC Advances ◽  
2014 ◽  
Vol 4 (78) ◽  
pp. 41484-41490 ◽  
Author(s):  
Mohammadreza Khanmohammadi ◽  
Keyvan Ghasemi ◽  
Amir Bagheri Garmarudi
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Basal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Basal Cell ◽  
Spectral Feature ◽  
Quadratic Discriminant Analysis ◽  
Sample Analysis ◽  
Blood Samples ◽  
Spectral Feature Selection

A diagnostic approach for basal cell carcinoma (BCC) has been developed based on investigation of the infrared spectra of blood samples.

scholarly journals Extremely Robust Remote-Target Detection Based on Carbon Dioxide-Double Spikes in Midwave Spectral Imaging

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2896 ◽  
Author(s):  
Sungho Kim ◽  
Jungsub Shin ◽  
Joonmo Ahn ◽  
Sunho Kim
Keyword(s):  
Carbon Dioxide ◽  
Fourier Transform ◽  
Target Detection ◽  
Emission Band ◽  
Co2 Emission ◽  
Spectral Feature ◽  
Spectral Imaging ◽  
Joint Analysis ◽  
Spectral Bands ◽  
Background Clutter

Infrared ship-target detection for sea surveillance from the coast is very challenging because of strong background clutter, such as cloud and sea glint. Conventional approaches utilize either spatial or temporal information to reduce false positives. This paper proposes a completely different approach, called carbon dioxide-double spike (CO2-DS) detection in midwave spectral imaging. The proposed CO2-DS is based on the spectral feature where a hot CO2 emission band is broader than that which is absorbed by normal atmospheric CO2, which generates CO2-double spikes. A directional-mean subtraction filter (D-MSF) detects each CO2 spike, and final targets are detected by joint analysis of both types of detection. The most important property of CO2-DS detection is that it generates an extremely low number of false positive caused by background clutter. Only the hot CO2 spike of a ship plume can penetrate atmosphere, and furthermore, there are only ship CO2 plume signatures in the double spikes of different spectral bands. Experimental results using midwave Fourier transform infrared (FTIR) in a remote sea environment validate the extreme robustness of the proposed ship-target detection.

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