Neural networks for the automated detection of methanol vapour from airborne passive infrared multispectral imaging data

References

• Anthimopoulos, M., S. Christodoulidis, L. Ebner, A. Christe, and S. Mougiakakou. 2016. “Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network.” IEEE Transactions on Medical Imaging 35: 1207–1216. doi:10.1109/TMI.2016.2535865.
   PubMed Web of Science ®Google Scholar
• Avery, T. E., and G. L. Berlin. 1992. Fundamentas of Remote Sensing and Airphoto Interpretation. New York: Macmillan.
   Google Scholar
• Berrueta, L. A., R. M. Alonso-Salces, and K. Héberger. 2007. “Supervised Pattern Recognition in Food Analysis.” Journal of Chromatography A 1158: 196–214. doi:10.1016/j.chroma.2007.05.024.
   PubMed Web of Science ®Google Scholar
• Chaffin, C. T., Jr., and T. L. Marshall. 1998. “Generating Well-characterized Chemical Plumes for Remote Sensing Research.” Paper presented at the SPIE Proceedings on Electro-optical Technology for Remote Chemical Detection and Identification III, Orlando, FL.
   Google Scholar
• Chang, P. P., J. R. Yang, W. Den, and C. Wu. 2014. “Characterizing and Locating Air Pollution Sources in a Complex Industrial District Using Optical Remote Sensing Technology and Multivariate Statistical Modeling.” Environmental Science and Pollution Research 21: 10852–10866. doi:10.1007/s11356-014-2962-0.
   PubMed Web of Science ®Google Scholar
• Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. J. Iacono, K. Cady-Pereira, S. Boukabara, and P. D. Brown. 2005. “Atmospheric Radiative Transfer Modeling: A Summary of the AER Codes.” Journal of Quantitative Spectroscopy and Radiative Transfer 91 (2): 233–244. doi:10.1016/j.jqsrt.2004.05.058.
   Web of Science ®Google Scholar
• Demuth, H. B., and M. H. Beale. 2001. Neural Network Toolbox for Use with MATLAB: Users Guide. Natick, MA: MathWorks.
   Google Scholar
• Fisher, R. A. 1970. Statistical Methods for Research Workers. 14th ed. Edinburgh: Oliver & Boyd.
   Google Scholar
• Gillespie, A., S. Rokugawa, J. Tsuneo Matsunaga, S. Cothern, S. Hook, and A. B. Kahle. 1998. “A Temperature and Emissivity Separation Algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Images.” IEEE Transactions on Geoscience and Remote Sensing 36: 1113–1126. doi:10.1109/36.700995.
   Web of Science ®Google Scholar
• Gillespie, A. R., T. Matsunaga, S. Rokugawa, and S. J. Hook. 1996. “Temperature and Emissivity Separation from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Images.” Paper presented at the SPIE Proceedings on Infrared Spaceborne Remote Sensing IV, Denver, CO, USA.
   Google Scholar
• Hua, L., and G. Shao. 2016. “The Progress of Operational Forest Fire Monitoring with Infrared Remote Sensing.” Journal of Forestry Research 28: 215–229. doi:10.1007/s11676-016-0361-8.
   Web of Science ®Google Scholar
• Hunter, A. 2000. “Feature Selection Using Probabilistic Neural Networks.” Neural Computing & Applications 9: 124–132. doi:10.1007/s005210070023.
   Web of Science ®Google Scholar
• Jain, A. K., and R. C. Dubes. 1988. Algorithms for Clustering Data. New Jersey: Prentice Hall.
   Google Scholar
• Jollife, I. T. 1986. Principal Component Analysis. New York: Springer-Verlag.
   Google Scholar
• Lippitt, C. D., D. A. Stow, and P. J. Riggan. 2016. “Application of the Remote-Sensing Communication Model to a Time-Sensitive Wildfire Remote-Sensing System.” International Journal of Remote Sensing 37: 3272–3292. doi:10.1080/01431161.2016.1196840.
   Web of Science ®Google Scholar
• MacKay, D. J. 2017. Information Theory, Inference, and Learning Algorithms. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Moller, M. F. 1993. “A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning.” Neural Networks 6: 525–533. doi:10.1016/S0893-6080(05)80056-5.
   Web of Science ®Google Scholar
• Rees, W. G. 2013. Physical Principles of Remote Sensing. 3rd ed. Cambridge, .K: Cambridge University Press.
   Google Scholar
• Scafutto, R. D., C. R. Filho, and B. Rivard. 2016. “Characterization of Mineral Substrates Impregnated with Crude Oils Using Proximal Inrared Hyperspectral Imaging.” Remote Sensing of Environment 179: 116–130. doi:10.1016/j.rse.2016.03.033.
   Web of Science ®Google Scholar
• Specht, D. F. 1990. “Probabilistic Neural Networks.” Neural Networks 3: 109–118. doi:10.1016/0893-6080(90)90049-Q.
   Web of Science ®Google Scholar
• Sulub, Y., and G. W. Small. 2008. “Simulated Radiance Profiles for Automating the Interpretation of Airborne Passive Multi-spectral Infrared Images.” Applied Spectroscopy 62 (10): 1049–1059. doi:10.1366/000370208786049150.
   PubMed Web of Science ®Google Scholar
• Tarumi, T., G. W. Small, R. J. Combs, and R. T. Kroutil. 2003. “Remote Detection of Heated Ethanol Plumes by Airborne Passive Fourier Transform Infrared Spectrometry.” Applied Spectroscopy 57: 1432–1441. doi:10.1366/000370203322554617.
   PubMed Web of Science ®Google Scholar
• Thomas, M. J., P. E. Lewis, R. T. Kroutil, R. J. Combs, R. B. Knapp, G. W. Small, R. W. Zywicki, D. L. Stageberg, C. T. Chaffin Jr., and T. L. Marshall. 2002. “Infrared Detection and Analysis of Vapor Plumes Using an Airborne Sensor.” Proceedings of SPIE - the International Society for Optical Engineering 4725: 47–64.
   Google Scholar
• Wabomba, M. J., Y. Sulub, and G. W. Small. 2007. “Remote Detection of Volatile Organic Compounds by Passive Multispectral Infrared Imaging Measurements.” Applied Spectroscopy 61: 349–358. doi:10.1366/000370207780466253.
   PubMed Web of Science ®Google Scholar
• Wan, B., and G. W. Small. 2008. “Airborne Passive Fourier Transform Infrared Remote Sensing of Methanol Vapor from Industrial Emissions.” The Analyst 133: 1776–1784. doi:10.1039/b802557f.
   PubMed Web of Science ®Google Scholar
• Wold, S., K. Esbensen, and P. Geladi. 1987. “Principal Component Analysis.” Chemometrics and Intelligent Laboratory Systems 2: 37–52. doi:10.1016/0169-7439(87)80084-9.
   Web of Science ®Google Scholar
• Yi, J., J. D. Wang, and G. Wang. 2016. “Improved Probabilistic Neural Networks with Self Adaptive Strategies for Transformer Fault Diagnosis Problem.” Advanced Mechanical Engineering 8: 1–13.
   Web of Science ®Google Scholar
• Zhang, L., and G. W. Small. 2002. “Automated Detection of Chemical Vapors by Pattern Recognition Analysis of Passive Multispectral Infrared Remote Sensing Imaging Data.” Applied Spectroscopy 56 (8): 1082–1093. doi:10.1366/000370202321274908.
   Web of Science ®Google Scholar
• Zywicki, R. W. 1999. “Radiometric Calibration of an Airborne Chemical Imager.” Proceedings of SPIE - the International Society for Optical Engineering 3537: 237–248.
   Google Scholar