Determine the Architecture of ANNs by Using the Peak Search Algorithm and Delta Values

Author(s):  
Mihirini Wagarachchi ◽  
Asoka Karunananda ◽  
Dinithi Navodya
Keyword(s):  
2006 ◽  
Vol 326-328 ◽  
pp. 305-308
Author(s):  
Sang Hwa Jeong ◽  
Gwang Ho Kim ◽  
Kyoung Rae Cha

With the increasing demand for VBNS and VDSL, the development of the kernel parts of optical communication such as PLC(Planar Light Circuit), Coupler, and WDM elements has increased. The optical transmitter and the receiver module need precise and mechanical alignment within a few micrometers to couple the semiconductor device, optical fiber and waveguide. The alignment and the attachment technology are very important in the fabrication of an optical element. Presently, the alignment of the optical element is time consuming, and an effective alignment algorithm has not yet to be developed. In this paper, the optical element alignment of the multi-axis ultra precision stage is studied. Two alignment algorithms applied to the ultra precision multi-axis stage are used, the field search algorithm and the peak search algorithm. The automation program to improve the characteristics of the optical element alignment system is developed by Labview programming and is composed of three tabs, the field search tab, plotting tab and peak search tab. The developed program is applied to an actual system to determine the improvement in alignment performance.


2021 ◽  
Author(s):  
Ruixin Liang ◽  
Liang Pan ◽  
Zhiyong Xing ◽  
Deng Pan ◽  
Xiaojun Yang ◽  
...  

2021 ◽  
Author(s):  
Baohua Zhang ◽  
Jinhui Zhu ◽  
XIAOQI Lu ◽  
Yu Gu ◽  
Jianjun Li ◽  
...  

Abstract To suppress background clutter and improve detection accuracy, this paper propose a dim target detection algorithm based on density peak search and region consistency. Firstly the density peak search algorithm is used to extract the candidate targets. And then the candidate targets are classified and marked according to the local mosaic probability factor, which is important to suppress the background clutter and accurately strip the candidate target region from the background. Considering the regional stability of the dim targets, local mosaic gradient factors are used to screen real targets from the candidate targets, and then facet kernel filter is used to extract the irregular contours of the dim targets, and as a result, the targets can be enhanced. The experimental results show that compared with the existing algorithms, the proposed method has better detection accuracy and stronger robustness in different complex scenarios.


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