[1]
|
许小京, 黄威. 光谱成像技术在物证鉴定领域的应用[J]. 红外与激光工程, 2012, 41(12): 3280-3284. doi: 10.3969/j.issn.1007-2276.2012.12.027XU Xiaojing, HUANG Wei. Application of spectral imaging in forensic science[J]. Infrared and Laser Engineering, 2012, 41(12): 3280-3284. doi: 10.3969/j.issn.1007-2276.2012.12.027
|
[2]
|
Edelman G J, Gaston E, Leeuwen T G van, et al. Hyperspectral imaging for non-contact analysis of forensic traces[J]. Forensic Science International, 2012, 223: 28-39. doi: 10.1016/j.forsciint.2012.09.012
|
[3]
|
Panagou E Z, Papadopoulou O, Carstensen J M, et al. Potential of multispectral imaging technology for rapid and non-destructive determination of the microbiological quality of beef filets during aerobic storage[J]. International Journal of Food Microbiology, 2014, 174: 1-11. doi: 10.1016/j.ijfoodmicro.2013.12.026
|
[4]
|
Belinda Bastide, Glenn Porter, Adrian Renshaw. Detection of Latent Bloodstains at Fire Scenes Using Reflected Infrared Photography[J]. Forensic Science International, 2019, 302: 109874 doi: 10.1016/j.forsciint.2019.109874
|
[5]
|
Zapata F, García-Ruiz C. Trac. Emerging spectrometric techniques for the forensic analysis of body fluids[J]. Trends in Analytical Chemistry, 2015, 64: 53-63.
|
[6]
|
张华锋, 王武, 白玉荣, 等. 多光谱成像无损识别冻融猪肉中危害级碎骨[J]. 光谱学与光谱分析, 2021, 41(9): 2892-2897. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN202109046.htmZHANG Huafeng, WANG Wu, BAI Yurong, et al. Non-destructive identification of hazardousbone fragments embedded in the frozen-thawed pork based on multispectral imaging[J]. Spectroscopy and Spectral Analysis, 2021, 41(9): 2892-2897. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN202109046.htm
|
[7]
|
Alsberg B K, Loke T, Baarstad I, et al. PryJector: a device for in situ visualization of chemical and physical property distributions on surfaces using projection and hyperspectral imaging[J]. Journal of Forensic Sciences, 2011, 56(4): 976-983. doi: 10.1111/j.1556-4029.2011.01747.x
|
[8]
|
Schuler R L, Kish P E, Plese C A. Preliminary observations on the ability of hyperspectral imaging to provide detection and visualization of bloodstain patterns on black fabrics[J]. Journal of Forensic Sciences, 2012, 57(6): 1562-1569. doi: 10.1111/j.1556-4029.2012.02171.x
|
[9]
|
Tahtouh M, Scott S A, Kalman J R, et al. Four novel alkyl 2-cyanoacylate monomers and their use in latent fingermark detection by mid-infrared spectral imaging[J]. Forensic Science International, 2011, 207(1-3): 223-238 doi: 10.1016/j.forsciint.2010.10.012
|
[10]
|
Joong Lee, Seong G Kong, Tae-Yi Kang, et al. Invisible ink mark detection in the visible spectrum using absorption difference[J]. Forensic Science International, 2014, 236: 77–83. doi: 10.1016/j.forsciint.2013.12.024
|
[11]
|
Edelman G, Manti V, van Ruth S M, et al. Identification and age estimation of blood stains on colored backgrounds by near infrared spectroscopy[J]. Forensic Science International, 2012, 220: 239-244. doi: 10.1016/j.forsciint.2012.03.009
|
[12]
|
Edelman G, van Leeuwen T G, Aalders M C. Hyperspectral imaging for non-contact analysis of forensic traces[J]. Forensic Science International, 2012, 223: 1-3. doi: 10.1016/j.forsciint.2012.04.012
|
[13]
|
Binu Melit Devassy, Sony George. Dimensionality reduction and visualisation of hyperspectral ink data using t-SNE[J]. Forensic Science International, 2020, 311: 109874.
|
[14]
|
Lívia Rodrigues e Brito, André Braz, Ricardo Saldanha Honorato, et al. Evaluating the potential of near infrared hyperspectral imaging associated with multivariate data analysis for examining crossing ink lines[J]. Forensic Science International, 2019, 298: 169-176. doi: 10.1016/j.forsciint.2019.02.043
|
[15]
|
Estelles-Lopez L, Ropodi A, Pavlidis D, et al. An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling[J]. Food Research International, 2017, 99: 206. doi: 10.1016/j.foodres.2017.05.013
|