Denoising Method of Inland AIS Information Based on Vessel Track

2012 ◽  
Author(s):  
Wen-juan Zhang ◽  
Qing Wu ◽  
Ling-zhi Sang ◽  
Zhe Mao
Keyword(s):  
Denoising Method

An image Denoising Method Based On Multi Resulation Bilateral Filter

2018 ◽  
Vol 6 (12) ◽  
pp. 448-452
Author(s):  
Md Shaiful Islam Babu ◽  
Kh Shaikh Ahmed ◽  
Md Samrat Ali Abu Kawser ◽  
Ajkia Zaman Juthi
Keyword(s):  
Image Denoising ◽  
Bilateral Filter ◽  
Denoising Method

Sonar image denoising method based on NSCT circle sample

2009 ◽  
Vol 29 (1) ◽  
pp. 68-70
Author(s):  
Chun-rui TANG ◽  
Dan-dan LIU
Keyword(s):  
Image Denoising ◽  
Denoising Method ◽  
Sonar Image

Improved anisotropic diffusion ultrasound image denoising method based on logarithmic compression

2013 ◽  
Vol 32 (11) ◽  
pp. 3218-3220
Author(s):  
Jin YANG ◽  
Zhi-qin LIU ◽  
Yao-bin WANG ◽  
Xiao-ming GAO
Keyword(s):  
Image Denoising ◽  
Anisotropic Diffusion ◽  
Ultrasound Image ◽  
Denoising Method

scholarly journals Objective Evaluation of Drivability in Passenger Cars with Dual-Clutch Transmission: A Case Study of Static Gearshift Condition

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Wei Zhou ◽  
Xuexun Guo ◽  
Xiaofei Pei ◽  
Chengcai Zhang ◽  
Jun Yan ◽  
...  
Keyword(s):  
Fuzzy Ahp ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Dual Clutch Transmission ◽  
Evaluation Tool ◽  
Passenger Cars ◽  
Denoising Method ◽  
Fuzzy Matrix ◽  
Predictability Score

This paper is aimed at the problem that the subjective drivability evaluation by experienced test drivers is limited in time efficiency and is of high cost and poor repeatability. In this article, an intelligent drivability objective evaluation tool (I-DOET) for passenger cars with dual-clutch transmission (DCT) is developed and verified by real vehicle testing. First, the signal denoising method and its key parameters, which are suitable for drivability evaluation, are selected based on analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). Besides, combined with the uncertainty characteristics of subjective judgment, a mathematical model of the objective drivability evaluation FARODE (fuzzy AHP-RS based on objective drivability evaluation) is proposed by using the fuzzy comprehensive assessment (FCA) method. The AHP and rough set (RS) method are used to calculate the subjective and objective weights of the drivability evaluation, respectively, and the proportion of subjective and objective weights is determined by the principle of minimum relative information entropy. The fuzzy matrix is built by membership function of the evaluation indexes. Finally, the static gearshift condition focused on by the subjective evaluation experts is taken as a case study. The predictability score is obtained by combining the drivability quantization lever vector, comprehensive weight, and fuzzy matrix. The experimental results indicate that the proposed method is applicable for objective drivability evaluation in passenger cars with DCT.

Infrared thermal imaging denoising method based on second-order channel attention mechanism

2021 ◽  
pp. 103789
Author(s):  
Zhuo Li ◽  
Shaojuan Luo ◽  
Meiyun Chen ◽  
Heng Wu ◽  
Tao Wang ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Second Order ◽  
Attention Mechanism ◽  
Denoising Method ◽  
Infrared Thermal Imaging

scholarly journals An image denoising method based on BP neural network optimized by improved whale optimization algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Chunzhi Wang ◽  
Min Li ◽  
Ruoxi Wang ◽  
Han Yu ◽  
Shuping Wang
Keyword(s):  
Neural Network ◽  
Image Denoising ◽  
Optimization Algorithm ◽  
Bp Neural Network ◽  
Weight Coefficient ◽  
Whale Optimization Algorithm ◽  
Denoising Method ◽  
Training Time ◽  
Whale Optimization ◽  
City Construction

AbstractAs an important part of smart city construction, traffic image denoising has been studied widely. Image denoising technique can enhance the performance of segmentation and recognition model and improve the accuracy of segmentation and recognition results. However, due to the different types of noise and the degree of noise pollution, the traditional image denoising methods generally have some problems, such as blurred edges and details, loss of image information. This paper presents an image denoising method based on BP neural network optimized by improved whale optimization algorithm. Firstly, the nonlinear convergence factor and adaptive weight coefficient are introduced into the algorithm to improve the optimization ability and convergence characteristics of the standard whale optimization algorithm. Then, the improved whale optimization algorithm is used to optimize the initial weight and threshold value of BP neural network to overcome the dependence in the construction process, and shorten the training time of the neural network. Finally, the optimized BP neural network is applied to benchmark image denoising and traffic image denoising. The experimental results show that compared with the traditional denoising methods such as Median filtering, Neighborhood average filtering and Wiener filtering, the proposed method has better performance in peak signal-to-noise ratio.

Rapid Response DAS Denoising Method Based on Deep Learning

2021 ◽  
Vol 39 (8) ◽  
pp. 2583-2593
Author(s):  
Maoning Wang ◽  
Lin Deng ◽  
Yuzhong Zhong ◽  
Jianwei Zhang ◽  
Fei Peng
Keyword(s):  
Deep Learning ◽  
Rapid Response ◽  
Denoising Method
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