SU-FF-J-57: A Phantom Study On the 3-D Target Localization Accuracy Using CBCT of An On-Board Imager

2007 ◽  
Vol 34 (6Part5) ◽  
pp. 2381-2381 ◽  
Author(s):  
L Zhang ◽  
H Yan ◽  
F Yin
2011 ◽  
Vol 268-270 ◽  
pp. 934-939
Author(s):  
Xue Wen He ◽  
Gui Xiong Liu ◽  
Hai Bing Zhu ◽  
Xiao Ping Zhang

Aiming at improving localization accuracy in Wireless Sensor Networks (WSN) based on Least Square Support Vector Regression (LSSVR), making LSSVR localization method more practicable, the mechanism of effects of the kernel function for target localization based on LSSVR is discussed based on the mathematical solution process of LSSVR localization method. A novel method of modeling parameters optimization for LSSVR model using particle swarm optimization is proposed. Construction method of fitness function for modeling parameters optimization is researched. In addition, the characteristics of particle swarm parameters optimization are analyzed. The computational complexity of parameters optimization is taken into consideration comprehensively. Experiments of target localization based on CC2430 show that localization accuracy using LSSVR method with modeling parameters optimization increased by 23%~36% in compare with the maximum likelihood method(MLE) and the localization error is close to the minimum with different LSSVR modeling parameters. Experimental results show that adapting a reasonable fitness function for modeling parameters optimization using particle swarm optimization could enhance the anti-noise ability significantly and improve the LSSVR localization performance.


2016 ◽  
Vol 31 (9) ◽  
pp. 902-912
Author(s):  
蔡明兵 CAI Ming-bing ◽  
王超 WANG Chao ◽  
刘晶红 LIU Jing-hong ◽  
周前飞 ZHOU Qian-fei ◽  
宋悦铭 SONG Yue-ming

2020 ◽  
Author(s):  
Dimitrios Dellios ◽  
Eleftherios P. Pappas ◽  
Ioannis Seimenis ◽  
Chryssa Paraskevopoulou ◽  
Kostas I. Lampropoulos ◽  
...  

1989 ◽  
Vol 41 (4) ◽  
pp. 747-773 ◽  
Author(s):  
Hermann J. Müller ◽  
Patrick M. A. Rabbitt

To study the processes underlying selective attention in visual search, the relation between the accuracy of “where” (location) and “what” (same/different orientation matching) decisions was analysed under various display conditions. Target-non-target discriminability was varied by contrasting single and multiple element displays; further, attention was directly manipulated by spatial cueing. In Experiment 1, analyses for both single and multiple displays showed that localization accuracy remained above chance when same/different matching failed; the inverse also obtained. It seems that accurate matching is not a prerequisite for target localization, nor is accurate localization a prerequisite for same/different matching. However, localization is a prerequisite for the accurate recognition of target orientation (Experiment 2). In this case, it seems that features critical for localization “call” attention to a particular candidate location. This facilitates further (shape) analysis of the stimulus that is found there. This orienting process is by-passed if attention is cued to the location in advance.


2011 ◽  
Vol 38 (6Part9) ◽  
pp. 3481-3481
Author(s):  
S Venkataraman ◽  
D Sasaki ◽  
J Butler ◽  
G Schroeder ◽  
M West ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Chenguang Shao

The target localization algorithm is critical in the field of wireless sensor networks (WSNs) and is widely used in many applications. In the conventional localization method, the location distribution of the anchor nodes is fixed and cannot be adjusted dynamically according to the deployment environment. The resulting localization accuracy is not high, and the localization algorithm is not applicable to three-dimensional (3D) conditions. Therefore, a Delaunay-triangulation-based WSN localization method, which can be adapted to two-dimensional (2D) and 3D conditions, was proposed. Based on the location of the target node, we searched for the triangle or tetrahedron surrounding the target node and designed the localization algorithm in stages to accurately calculate the coordinate value of the target. The relationship between the number of target nodes and the number of generated graphs was analysed through numerous experiments, and the proposed 2D localization algorithm was verified by extending it the 3D coordinate system. Experimental results revealed that the proposed algorithm can effectively improve the flexibility of the anchor node layout and target localization accuracy.


2015 ◽  
Vol 42 (6) ◽  
pp. 3270-3270
Author(s):  
J Briceno ◽  
H Li ◽  
Y Huang ◽  
N Wen ◽  
I Chetty

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