New variants of Bennett variance method with correlation indices for reducing delayed-neutron contribution

2020 ◽  
Vol 148 ◽  
pp. 107696
Author(s):  
Yasunori Kitamura ◽  
Tsuyoshi Misawa
2007 ◽  
Vol 75 (5) ◽  
Author(s):  
J. L. Lou ◽  
Z. H. Li ◽  
Y. L. Ye ◽  
H. Hua ◽  
D. X. Jiang ◽  
...  

1988 ◽  
Vol 64 (6) ◽  
pp. 487-489
Author(s):  
B. P. Maksyutenko ◽  
Yu. F. Balakshev ◽  
S. V. Ignat'ev
Keyword(s):  

2021 ◽  
Vol 382 ◽  
pp. 111372
Author(s):  
Abhitab Bachchan ◽  
K. Devan ◽  
K. Yernamma ◽  
M. Alagan ◽  
K. Natesan ◽  
...  
Keyword(s):  

2002 ◽  
Vol 41 (1-4) ◽  
pp. 317-359 ◽  
Author(s):  
E. Fort ◽  
V. Zammit-Averlant ◽  
M. Salvatores ◽  
A. Filip ◽  
J-F Lebrat

2013 ◽  
Vol 798-799 ◽  
pp. 761-764
Author(s):  
Ming Xia Xiao

A new technique that combines maximum variance method and morphology was presented for Synthetic Aperture Radar (SAR) image segmentation in target detection. Firstly, using the first-order differential method to enhance the original image for highlighting edge details of the image; then using the maximum variance method to calculate the gray threshold and segment the image; lastly, the mathematical morphology was used to processing the segmented image, which could prominently improve the segmentation effects. Experiments show that this algorithm can obtain accurate segmentation results, and have a good effect on noise suppression, edge detail protection and operation time.


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