Adversarial Perturbation Suppression using Adaptive Gaussian Smoothing and Color Reduction

Author(s):  
Li-Yun Wang
2012 ◽  
Vol 21 (10) ◽  
pp. 1250080
Author(s):  
JAKUB MIELCZAREK ◽  
MICHAŁ KAMIONKA

In this paper, we investigate power spectrum of a smoothed scalar field. The smoothing leads to regularization of the UV divergences and can be related with the internal structure of the considered field or the space itself. We perform Gaussian smoothing to the quantum fluctuations generated during the phase of cosmic inflation. We study whether this effect can be probed observationally and conclude that the modifications of the power spectrum due to the smoothing on the Planck scale are negligible and far beyond the observational abilities. Subsequently, we investigate whether smoothing in any other form can be probed observationally. We introduce phenomenological smoothing factor e-k2σ2 to the inflationary spectrum and investigate its effects on the spectrum of CMB anisotropies and polarization. We show that smoothing can lead to suppression of high multipoles in the spectrum of the CMB. Based on seven years observations of WMAP satellite we indicate that the present scale of high multipoles suppression is constrained by σ < 3.19 Mpc (95% CL). This corresponds to the constraint σ < 100 μm at the end of inflation. Despite this value is far above the Planck scale, other processes of smoothing can be possibly studied with this constraint, as decoherence or diffusion of primordial perturbations.


Author(s):  
Xiao Jiang ◽  
Zhongjian Tian ◽  
Xingxiang Ji ◽  
Hao Ma ◽  
Guihua Yang ◽  
...  

2018 ◽  
Vol 7 (4.33) ◽  
pp. 487
Author(s):  
Mohamad Haniff Harun ◽  
Mohd Shahrieel Mohd Aras ◽  
Mohd Firdaus Mohd Ab Halim ◽  
Khalil Azha Mohd Annuar ◽  
Arman Hadi Azahar ◽  
...  

This investigation is solely on the adaptation of a vision system algorithm to classify the processes to regulate the decision making related to the tasks and defect’s recognition. These idea stresses on the new method on vision algorithm which is focusing on the shape matching properties to classify defects occur on the product. The problem faced before that the system required to process broad data acquired from the object caused the time and efficiency slightly decrease. The propose defect detection approach combine with Region of Interest, Gaussian smoothing, Correlation and Template Matching are introduced. This application provides high computational savings and results in better recognition rate about 95.14%. The defects occur provides with information of the height which corresponds by the z-coordinate, length which corresponds by the y-coordinate and width which corresponds by the x-coordinate. This data gathered from the proposed system using dual camera for executing the three dimensional transformation.  


2019 ◽  
Vol 64 (1) ◽  
pp. 305-312 ◽  
Author(s):  
Roland Hostettler ◽  
Simo Sarkka
Keyword(s):  

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