scholarly journals Recent progress on X-ray security inspection technologies

2017 ◽  
Vol 62 (13) ◽  
pp. 1350-1364
Author(s):  
ZhiQiang CHEN ◽  
Li ZHANG ◽  
Xin JIN
1986 ◽  
Vol 47 (C6) ◽  
pp. C6-23-C6-30 ◽  
Author(s):  
S. SUCKEWER ◽  
C. H. SKINNER ◽  
D. KIM ◽  
E. VALEO ◽  
D. VOORHEES ◽  
...  

2021 ◽  
Vol 11 (7) ◽  
pp. 2971
Author(s):  
Siwei Tao ◽  
Congxiao He ◽  
Xiang Hao ◽  
Cuifang Kuang ◽  
Xu Liu

Numerous advances have been made in X-ray technology in recent years. X-ray imaging plays an important role in the nondestructive exploration of the internal structures of objects. However, the contrast of X-ray absorption images remains low, especially for materials with low atomic numbers, such as biological samples. X-ray phase-contrast images have an intrinsically higher contrast than absorption images. In this review, the principles, milestones, and recent progress of X-ray phase-contrast imaging methods are demonstrated. In addition, prospective applications are presented.


2000 ◽  
Vol 55 (1-2) ◽  
pp. 291-297 ◽  
Author(s):  
T. J. Bastow

Some recent progress in solid state 47,49Ti NMR is described and reviewed. The metallic-state work described covers metals such as hep titanium, TiB2 , a number of intermetallics such as TiAl2 and TiAl3· The inorganic work covers the various titanium oxide based materials including the TiO2 polymorphs, anatase, rutile and brookite. The gel work covers the evolution of crystalline titania from gels formed by hydrolysis of titanium isopropoxide. Some complementary data from 17O and 13C NMR and powder X-ray diffraction is also included.


Author(s):  
A. Klisnick ◽  
D. Ros ◽  
G. Jamelot ◽  
S. Kazamias ◽  
M. Pitmann ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yong Zhang ◽  
Weiwu Kong ◽  
Dong Li ◽  
Xudong Liu

We present an X-ray material classifier region-based convolutional neural network (XMC R-CNN) model for detecting the typical guns and the typical knives in X-ray baggage images. The XMC R-CNN model is used to solve the problem of contraband detection in overlapped X-ray baggage images by the X-ray material classifier algorithm and the organic stripping and inorganic stripping algorithm, and better detection rate and the miss rate are achieved. The detection rates of guns and knives are 96.5% and 95.8%, and the miss rates of guns and knives are 2.2% and 4.2%. The contraband detection technology based on the XMC R-CNN model is applied to X-ray baggage images of security inspection. According to user needs, the safe X-ray baggage images can be automatically filtered in some specific fields, which reduces the number of X-ray baggage images that security inspectors need to screen. The efficiency of security inspection is improved, and the labor intensity of security inspection is reduced. In addition, the security inspector can screen X-ray baggage images according to the boxes of automatic detection, which can improve the effect of security inspection.


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