scholarly journals Background reduction at DTU Nutech surface gamma laboratory

2019 ◽  
Vol 151 ◽  
pp. 30-38
Author(s):  
Nikola Marković ◽  
Per Roos ◽  
Sven Poul Nielsen ◽  
Xiao Xiao Cai
Keyword(s):  
Background Reduction

Surface Sensitive Bolometer for the CUORE background reduction

2005 ◽  
Vol 143 ◽  
pp. 510
Author(s):  
M. Pedretti ◽  
L. Foggetta ◽  
A. Giuliani ◽  
C. Nones ◽  
S. Sangiorgio
Keyword(s):  
Background Reduction

isoSTED microscopy with water-immersion lenses and background reduction

2021 ◽  
Author(s):  
René Siegmund ◽  
Frank Werner ◽  
Stefan Jakobs ◽  
Claudia Geisler ◽  
Alexander Egner
Keyword(s):  
Water Immersion ◽  
Background Reduction

scholarly journals Optimization of Liquid Scintillation Counting Conditions With Two Kinds of Vials and Detector Shields for Low-Activity Radiocarbon Measurements

Radiocarbon ◽  
1989 ◽  
Vol 31 (03) ◽  
pp. 380-386 ◽  
Author(s):  
Gemma Rauret ◽  
J S Mestres ◽  
J F Garcia
Keyword(s):  
Working Conditions ◽  
Spectrum Analysis ◽  
Liquid Scintillation ◽  
Three Dimensional ◽  
Pulse Height ◽  
Quality Parameters ◽  
Scintillation Counting ◽  
Background Reduction ◽  
Low Activity ◽  
Bias Selection

Low-level radiocarbon measurements were made using two liquid scintillation (LS) counters, both with passive lead shields of approximately the same dimensions. The first one had a conventional background reduction with low-activity lead and “high-low” coincidence bias selection, and the second one had a spectrum analysis background reduction based on the different three-dimensional pulse-height signal of background and beta pulses. The performance of commercial teflon-copper and glass vials were compared with both LS counters. Optimum counting conditions for the two detectors studied were also established. From results obtained, quality parameters and characteristics of quench curves were studied. Performances of each counter in the working conditions established were also compared.

scholarly journals A novel background reduction strategy for high level triggers and processing in gamma-ray Cherenkov detectors

2008 ◽  
Author(s):  
G. Cabras ◽  
A. De Angelis ◽  
B. De Lotto ◽  
M. M. De Maria ◽  
F. De Sabata ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Cherenkov Detectors ◽  
Reduction Strategy ◽  
Background Reduction ◽  
High Level

scholarly journals Aluminum abundance on the surface of Mercury: Application of a new background-reduction technique for the analysis of gamma-ray spectroscopy data

2012 ◽  
Vol 117 (E12) ◽  
pp. n/a-n/a ◽  
Author(s):  
Patrick N. Peplowski ◽  
Edgar A. Rhodes ◽  
David K. Hamara ◽  
David J. Lawrence ◽  
Larry G. Evans ◽  
...  
Keyword(s):  
Gamma Ray ◽  
Reduction Technique ◽  
Spectroscopy Data ◽  
Background Reduction ◽  
Gamma Ray Spectroscopy

scholarly journals Stochastic heating by ECR as a novel means of background reduction in the KATRIN spectrometers

2012 ◽  
Vol 7 (08) ◽  
pp. P08025-P08025 ◽  
Author(s):  
S Mertens ◽  
A Beglarian ◽  
L Bornschein ◽  
G Drexlin ◽  
F M Fränkle ◽  
...  
Keyword(s):  
Background Reduction ◽  
Stochastic Heating

Background reduction in germanium spectrometers: Material selection, geometry, and shielding

1984 ◽  
Vol 223 (2-3) ◽  
pp. 420-425 ◽  
Author(s):  
H.L. Malm ◽  
M.M. Watt ◽  
I. Bostock ◽  
J.L. Campbell ◽  
P. Jagam ◽  
...  
Keyword(s):  
Material Selection ◽  
Background Reduction

The Target Motion Detection Algorithm Based on Gauss Mixture Model

2012 ◽  
Vol 468-471 ◽  
pp. 1421-1425 ◽  
Author(s):  
Qiu Chan Bai ◽  
Chun Xia Jin ◽  
Ding Li Yang ◽  
Ma Hua Wang
Keyword(s):  
Gaussian Mixture ◽  
Detection Algorithm ◽  
Small Time ◽  
Moving Target ◽  
Background Region ◽  
Background Reduction ◽  
Foreground Region ◽  
Background Extraction ◽  
Gauss Mixture ◽  
Background Image

Background reduction technique not only has the characteristics of pixels identify changes and small time complexity, but also can provide better detection results. The paper puts forward the running average method constructing background image by Gaussian mixture mode detecting background region and foreground region, and then adopting background reduction realizes the detection of moving target. Experimental results show that the algorithm effectively may realize background extraction and updating, and then completely and accurately detects moving targets. The algorithm has been achieved good results in the video vehicle detection.

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