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Research and implementation of real-time transmission technology for industrial interconnection 工业互联实时传输技术的研究与实现
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824933
Zhen He, Liang Ye
{"title":"Research and implementation of real-time transmission technology for industrial interconnection","authors":"Zhen He, Liang Ye","doi":"10.1109/cvidliccea56201.2022.9824933","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824933","url":null,"abstract":"Traditional service methods can not guarantee the development needs of IP network. Aiming at this problem, this paper designs a transmission mechanism based on virtual network slicing and time sensitivity differentiation. By distinguishing the QoS requirements of different services, the time sensitive flow can be forwarded first, so as to ensure that the time sensitive flow can obtain the maximum QoS guarantee through the optimal forwarding path. The experimental results show that the transmission method used in this paper can better balance the network load and improve the resource utilization of the network.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"52 1","pages":"1133-1136"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90974783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Novel Generative Adversarial Network simulating the complementary structure of DNA genetic information 一种模拟DNA遗传信息互补结构的新型生成对抗网络
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9825138
Lei Zhang, Haoying Wu
{"title":"A Novel Generative Adversarial Network simulating the complementary structure of DNA genetic information","authors":"Lei Zhang, Haoying Wu","doi":"10.1109/cvidliccea56201.2022.9825138","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9825138","url":null,"abstract":"To solve the problems of mode collapse and training instability in generative adversarial networks (GANs), a framework simulating the complementary structure of DNA is proposed, in which a complementary unit and a generalization unit are added. Four latent vectors representing four bases of A, T,C and G are obtained from the complementary unit. Through the combination of latent vectors, the generalization unit avoids the fitting of high-dimensional data distribution and obtains a more comprehensive vector space. Experimental results show that the problems of model collapse and training instability are effectively solved, compared with state-of-the-art VAE-GAN, the FID score increases 52.2%, indicating that the quality and diversity of images generated by the model are improved.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"1 1","pages":"9-14"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90463070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Exploring a Computer Vision and Artificial Intelligence-based Approach to Sit-and-reach Distance Measurement 基于计算机视觉和人工智能的坐姿距离测量方法研究
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9825271
Cheng Jiang, JiaQi Sun, Kexin Qi, Cheng Jin, GangTie Jin
{"title":"Exploring a Computer Vision and Artificial Intelligence-based Approach to Sit-and-reach Distance Measurement","authors":"Cheng Jiang, JiaQi Sun, Kexin Qi, Cheng Jin, GangTie Jin","doi":"10.1109/cvidliccea56201.2022.9825271","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9825271","url":null,"abstract":"The key technique of sit-and-reach distance measurement in this study mainly consists of two stages: the first stage is the initial calibration of the test site, including camera calibration, identification and calibration of the test site identification points and finger key points; the second stage is the distance measurement stage, including the calculation of the coordinates of the finger tip to the scale projection point of the suspended distance measurement and the calculation of the conversion distance of the projection point. After the validity test of ranging, the error was 0. 148cm with standard deviation of 0.118, maximum value of 0.495, and minimum value of 0.002 for 90 experiments, which proved that the research results had high ranging accuracy. Since this study uses a common webcam, the method is easy to be widely used.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"1 1","pages":"225-229"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89766635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
General nonlinear function neural network fitting algorithm based on CNN 基于CNN的一般非线性函数神经网络拟合算法
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824846
Xintao Xu, Zhelong Jiang, Gang Chen, Zhigang Li, Guoliang Gong, Huaxiang Lu
{"title":"General nonlinear function neural network fitting algorithm based on CNN","authors":"Xintao Xu, Zhelong Jiang, Gang Chen, Zhigang Li, Guoliang Gong, Huaxiang Lu","doi":"10.1109/cvidliccea56201.2022.9824846","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824846","url":null,"abstract":"This paper proposes a generic neural network fitting algorithm based on CNN for nonlinear functions that overcomes the challenges of a large number of nonlinear functions in terms of hardware deployment and computing circuit generality in diverse neural network models. The model takes advantage of the principle that functions have varying degrees of difficulty fitting in different spaces, mapping the input to high-dimensional space with 1x1 convolution, and utilizing CNN to extract features of nonlinear functions with its strong feature extraction ability in high-dimensional space. Furthermore, MaxPool and ReLU improve the ability of nonlinear fitting. When fitting Tanh, Sigmoid, and ELU activation functions with 16bit accuracy, the proposed algorithm has an average error of less than 0.0006, with a parameter size of 5.793 k.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"65 1","pages":"1079-1082"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86519190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design Method of Universal Modular Digital Target Simulation System 通用模块化数字目标仿真系统的设计方法
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9825333
Yong Sun, W. Yang, Guangzhao Lu, Jinqing Zhao, Xiaoyue Wang, Ji-rong Xue
{"title":"Design Method of Universal Modular Digital Target Simulation System","authors":"Yong Sun, W. Yang, Guangzhao Lu, Jinqing Zhao, Xiaoyue Wang, Ji-rong Xue","doi":"10.1109/cvidliccea56201.2022.9825333","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9825333","url":null,"abstract":"This paper presents a design method of general modular digital target simulation system, and realizes the software based on this method. This method includes target vulnerability model import sub module and target vulnerability model construction sub module. It mainly completes the import or construction of target vulnerability model, target location determination, shape feature identification, identification of key components and non-key components, division of killing mode of key components, establishment of geometric model of components, etc. It can provide target vulnerability related data for damage effectiveness evaluation and fire plan.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"192 1","pages":"931-934"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89085861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Non-frontal face recognition method with a side-face-correction generative adversarial networks 基于侧脸校正生成对抗网络的非正面人脸识别方法
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9825237
Haixin Lin, Hongzhi Ma, Weibin Gong, Chao Wang
{"title":"Non-frontal face recognition method with a side-face-correction generative adversarial networks","authors":"Haixin Lin, Hongzhi Ma, Weibin Gong, Chao Wang","doi":"10.1109/cvidliccea56201.2022.9825237","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9825237","url":null,"abstract":"Frontal face image recognition is the main target of traditional face recognition.The deflection of the human face often causes the dislocation of the facial features,which leads to the reduction of the recognition accuracy of the non-frontal face.To solve the above problems,a non-frontal face recognition model based on generative adversarial network is proposed.In this model,the angle information is encoded separately by using a two-channel generator and auto-coding network,and the non-frontal face image in natural environment is corrected to obtain the frontal face image.Through the multi-discriminator mechanism of facial attention,we set discriminators in the eye, eyebrow, nose, mouth and the whole area of the face image so as to retain the details of the face to the maximum extent while ensuring the clarity of image.Then the corrected face features are extracted by Facenet and MTCNN to obtain the non-frontal face recognition results.The model is validated on multi-PIE dataset and CFP dataset.The results show that the accuracy of non-frontal face recognition is improved by 1% in CFP dataset compared with VGG-FACE, TP- CNN and HPN.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"625 1","pages":"563-567"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78971103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Identification Method of Dress Pattern Drawing based on Machine Vision Algorithm 基于机器视觉算法的服装图案识别方法
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824224
Keun-Jong Lyu, Haizhang Yan
{"title":"Identification Method of Dress Pattern Drawing based on Machine Vision Algorithm","authors":"Keun-Jong Lyu, Haizhang Yan","doi":"10.1109/cvidliccea56201.2022.9824224","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824224","url":null,"abstract":"This paper uses the machine vision method to identify the skirt module. We have constructed three kinds of machine recognition models of skirt profile processing, structure analysis of style drawing, and size estimation. The author constructs a relatively complete image recognition system for dress pattern drawing. In addition, we conducted an effect evaluation with a certain number of samples at the later stage of the experiment. This study has A good effect in distinguishing an A-type skirt from an H-type skirt, identifying the reasonable degree and length of the skirt, and determining the quantity statistics of each component element in the skirt pattern diagram.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"32 1","pages":"76-79"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76514713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Book recommendation system based on an optimized collaborative filtering algorithm 基于优化协同过滤算法的图书推荐系统
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824088
Yujie Lu, Yidi Lu
{"title":"Book recommendation system based on an optimized collaborative filtering algorithm","authors":"Yujie Lu, Yidi Lu","doi":"10.1109/cvidliccea56201.2022.9824088","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824088","url":null,"abstract":"Collaborative filtering is widely applied in recommendation systems. The traditional method usually adopts the cosine similarity algorithm or Pearson algorithm, but a sparse rating matrix may lead to inaccurate recommendation results. The optimized algorithm adds penalty terms according to the number of score vector elements to reduce the impact of sparsity. More purchase behaviors are taken into account in the optimization algorithm, including user activity, product popularity, and the time cost of user preferences. Due to the validity of the data set, the top-k method is adopted to select k users with the highest similarity (1) as the recommendation basis. Compared with the traditional method, the numerical results have a lower root mean squared error, and the algorithm execution time is significantly shortened. The optimized collaborative filtering algorithm can effectively alleviate the impact of sparsity and consider more purchasing behaviors, thus improving the algorithm efficiency and rating reliability of the book recommendation system.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"74 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74089388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Blockchain-based power battery traceability system for new energy vehicles 基于区块链的新能源汽车动力电池溯源系统
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824472
Yan Ma, Ruoyu Fang
{"title":"Blockchain-based power battery traceability system for new energy vehicles","authors":"Yan Ma, Ruoyu Fang","doi":"10.1109/cvidliccea56201.2022.9824472","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824472","url":null,"abstract":"In response to the problems of the traditional new energy vehicle power battery traceability system such as centralized easy tampering, data cannot be shared and lack of effective management, this paper proposes a blockchain-based new energy vehicle power battery supply chain traceability system. Analyzed the business processes in the power battery supply chain of production, vehicle, sales, power exchange and recycling, designed the system architecture according to the different needs of regulators, consumers, enterprises and other subjects, established the traceability information chain and database, and proposed a smart contract applicable to the system. The system relies on the characteristics of blockchain decentralization and on-chain data that cannot be tampered with, which protects the privacy of users and improves the reliability of the system while meeting the traceability needs of power batteries.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"16 1","pages":"248-251"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88432935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Hyperspectral Image Denoising Based on Multi-Resolution Gated Network with Wavelet Transform 基于小波变换的多分辨率门控网络高光谱图像去噪
Vision Pub Date : 2022-05-20 DOI: 10.1109/cvidliccea56201.2022.9824964
Kengpeng Li, Fenfa Zhong, Lei Sun
{"title":"Hyperspectral Image Denoising Based on Multi-Resolution Gated Network with Wavelet Transform","authors":"Kengpeng Li, Fenfa Zhong, Lei Sun","doi":"10.1109/cvidliccea56201.2022.9824964","DOIUrl":"https://doi.org/10.1109/cvidliccea56201.2022.9824964","url":null,"abstract":"Hyperspectral image denoising is an essential pre-processing task. In this paper, a multi-resolution gated network based on wavelet transform (WMRGNet) is proposed for removing mixed noise of hyperspectral images. Firstly, based on the fact that hyperspectral images have strong spectral correlation, a spatial-spectral information extraction module is designed to use the current noisy band and its adjacent bands as the input of WMRGNet. Secondly, aim to fully consider the spatial local and global information of hyperspectral images, a multi-resolution feature extraction module is proposed, applying the discrete wavelet transform to divide the resolution into four scales, and the residual blocks to extract information of different resolutions. In addition, a gated layer is introduced for cross-resolution information interaction to enhance the feature fusion. Finally, a high-resolution image reconstruction module with multiple residual blocks is employed to extract high-resolution features. In the simulated data set experiments, WMRGNet removes Gaussian, stripe and deadline noise and preserves the detailed information of the hyperspectral images.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"56 1","pages":"637-642"},"PeriodicalIF":0.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88935014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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