2021 International Symposium on Computer Technology and Information Science (ISCTIS)最新文献

Automatic grasping of 3-DOF robotic arm based on visual feedback 基于视觉反馈的三自由度机械臂自动抓取

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00025

Yuming Li, Qi Zhang, Xiao Li, Ziyi Li, Xiwei Zhang

引用次数: 0

Resolvable cluster target tracking based on wavelet coefficients and JPDA 基于小波系数和JPDA的可分辨聚类目标跟踪

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00074

Xirui Xue, Shucai Huang, Ning Li, Weijie Zhong

引用次数: 2

Research on the Digital Design Method for Core module Functional Verification Platform 核心模块功能验证平台数字化设计方法研究

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00024

YanXia Gao, Peng Wei, Xingheng Jia, Chen Cao

{"title":"Research on the Digital Design Method for Core module Functional Verification Platform","authors":"YanXia Gao, Peng Wei, Xingheng Jia, Chen Cao","doi":"10.1109/ISCTIS51085.2021.00024","DOIUrl":"https://doi.org/10.1109/ISCTIS51085.2021.00024","url":null,"abstract":"In this paper, considering the sufficiency of the verification of functions and interfaces between a large space station system, a digital design method is used to research and design a verification platform, innovatively combining aluminum profiled materials and aluminum honeycomb panel materials, through special profiled corners. Pieces are connected and built to complete the entire structural design. Using this platform structure to perform AIT pre-test verification on a core module, which can find out the problems of a core module system level, complete device level, and inter-segment functions and interfaces as early as possible, and can verify the correctness of the space station system-level electrical functions in advance And rationality, effectively compress the system function test time in the AIT stage, and make up for the shortcomings of current traditional verification platform for the lack of verification of certain functions of whole device. In this paper, the structural module of the verification platform is designed and analyzed in detail, and the safety and reliability of the overall structure of verification platform are calculated and verified by the NASTRAN finite element analysis software. After practical application, the innovation and feasibility of the platform are further verified. It is worth promoting.","PeriodicalId":403102,"journal":{"name":"2021 International Symposium on Computer Technology and Information Science (ISCTIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126871188","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

Grey Theory Based Model Applied in Carbon Emissions Prediction for The Chengdu-Chongqing Twin Cities Economic Zone 灰色模型在成渝双城经济区碳排放预测中的应用

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00038

Kun Wang, Ling Xiao

引用次数: 2

Research on Digital Image Recognition Algorithm Based on Pattern Recognition 基于模式识别的数字图像识别算法研究

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00085

Shu-Feng Di

引用次数: 0

A Research on Face Recognition Open Source Development Framework Based on PyTorch 基于PyTorch的人脸识别开源开发框架研究

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00077

Xinghan Huang, Xiaofu Du, Hedan Liu, Wenkai Zang

{"title":"A Research on Face Recognition Open Source Development Framework Based on PyTorch","authors":"Xinghan Huang, Xiaofu Du, Hedan Liu, Wenkai Zang","doi":"10.1109/ISCTIS51085.2021.00077","DOIUrl":"https://doi.org/10.1109/ISCTIS51085.2021.00077","url":null,"abstract":"At present, there are some problems in the development framework of various neural networks for face recognition in the laboratory environment, for example, the development environment is not standard, the dataset is not standard, and it is not friendly to beginners. In order to solve the above problems, this paper presents an open-source face recognition research and development framework based on PyTorch to help beginners quickly complete the experimental environment. First, based on the current mainstream CUDA technology, combined with PyTorch machine learning library, and with general third-party libraries such as OpenCV, a face recognition research and development framework is built. Then, a custom image data collection acquisition mechanism with three-tier filtering capabilities is proposed to help users quickly obtain high-quality datasets for use by the R&D framework. In addition, based on this research and development framework, some methods such as model compression, parameter sharing, were used to speed up model training. Finally, two classical experiments of handwritten numeric recognition and face recognition are implemented in this research and development framework. The test results show that the R&D framework is easy to use and has high practical value.","PeriodicalId":403102,"journal":{"name":"2021 International Symposium on Computer Technology and Information Science (ISCTIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126264318","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

Research on Flight Type Recognition Technology Based on Information Fusion 基于信息融合的飞行类型识别技术研究

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00053

Zhi-xiong Guo, Gang Chen, Yongwang Tang, Han Wei, Liuyang Yu, Yiwei Feng

引用次数: 0

The Influence of Deflector Form on Airflow Organization in Prefabricated Duct Elbows Based on CFD Simulation 基于CFD模拟的预制风管弯头导流板形式对气流组织的影响

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00080

Tang Yi, Pan Jian, Cao Xiaocheng, Niu Zhihai, Chen Xiaoweng

引用次数: 0

Research on the Application of Knowledge Graph in the Integrated Course STEAM 知识图谱在集成课程STEAM中的应用研究

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00087

Gao Baoling, Lin Tao

引用次数: 0

Wafer maps defect recognition based on transfer learning of handwritten pre-training network 基于迁移学习的手写体预训练网络晶圆图缺陷识别

2021 International Symposium on Computer Technology and Information Science (ISCTIS) Pub Date : 2021-06-01 DOI: 10.1109/ISCTIS51085.2021.00064

Shouhong Chen, Yuxuan Zhang, Mulan Yi, Jun Ma, Xingna Hou

{"title":"Wafer maps defect recognition based on transfer learning of handwritten pre-training network","authors":"Shouhong Chen, Yuxuan Zhang, Mulan Yi, Jun Ma, Xingna Hou","doi":"10.1109/ISCTIS51085.2021.00064","DOIUrl":"https://doi.org/10.1109/ISCTIS51085.2021.00064","url":null,"abstract":"A new method of defect recognition based on handwriting classification pre-training transfer learning is proposed for efficient defect recognition of wafer maps. Using deep learning can better identify wafer map defects, but one problem that a large amount of training data is needed to build a deep network model that can effectively recognize complex images. Another problem is the uneven distribution of the number of defect types in the wafer map during the actual manufacturing process. To solve these two problems, this paper uses the deep convolutional neural network trained in the MNIST dataset for handwriting classification as a pre-trained network for transfer learning. Since the MNIST data set contains simple basic patterns such as lines and circles that are common in the defect mode of wafer maps, the training of a deep network requires fewer data. Moreover, transfer learning reduces the amount of data for deep network training by transferring the parameters of the pre-trained network to the pattern recognition and classification model of wafer maps. This method uses a tenfold cross-validation method to verify multiple sets of different size subsets of the WM811K data set. The average recognition accuracy of each group of 10 experiments is above 94.9%. It has good recognition effect.","PeriodicalId":403102,"journal":{"name":"2021 International Symposium on Computer Technology and Information Science (ISCTIS)","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133176504","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: 2