2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)最新文献_第5页

Human-Computer Interface Design Based on Design Psychology 基于设计心理学的人机界面设计

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00009

Yina Liu

{"title":"Human-Computer Interface Design Based on Design Psychology","authors":"Yina Liu","doi":"10.1109/ICHCI51889.2020.00009","DOIUrl":"https://doi.org/10.1109/ICHCI51889.2020.00009","url":null,"abstract":"In this new era of rapid development, product design not only needs to meet some mechanical and practical needs, but also needs to meet people’s emotional and psychological design needs. In the past, the traditional human-computer interaction interface can not meet the needs of people for human-computer interaction interface in the current era, so it is necessary to integrate some psychological design content. Therefore, in order to improve the user’s experience of human-computer interaction interface, this paper puts forward the research method of human-computer interaction interface design based on design psychology. On some related problems of psychology, this paper analyzes some practical problems in the design of human-computer interaction interface based on design psychology from the aspects of human action and perception, and according to the design psychology After that, the proportion of different feelings in human-computer information received by human beings and the factors concerned by Chinese users in the process of human-computer interface operation are investigated. The results show that people have new requirements for human-computer interaction interface design The experimental data and results, so as to develop a set of suitable for the new era of human-computer interaction interface design research based on design psychology.","PeriodicalId":355427,"journal":{"name":"2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121402628","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: 4

Knowledge Graph construction of Thangka icon characters based on Neo4j 基于Neo4j的唐卡图标字符知识图谱构建

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00054

Sujie Cheng, Tiejun Wang, Xiaoran Guo, Yu Wang

引用次数: 3

Virtual Reality Games based on Brain Computer Interface 基于脑机接口的虚拟现实游戏

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00056

Rongxiang Zhang

引用次数: 4

Analysis of multimedia application and research based on web pages 基于网页的多媒体应用分析与研究

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00031

Ming Liu, Xiaoping Huang

引用次数: 1

Research on the Application of Data Encryption Technology in Computer Network Communication Security 数据加密技术在计算机网络通信安全中的应用研究

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00044

Kuiliang Xia, Xiaoming Song

引用次数: 0

Unmanned Aerial Vehicle Classification and Detection Based on Deep Transfer Learning 基于深度迁移学习的无人机分类与检测

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00067

W. Meng, Meng Tia

{"title":"Unmanned Aerial Vehicle Classification and Detection Based on Deep Transfer Learning","authors":"W. Meng, Meng Tia","doi":"10.1109/ICHCI51889.2020.00067","DOIUrl":"https://doi.org/10.1109/ICHCI51889.2020.00067","url":null,"abstract":"Currently, major security incidents caused by the “unlicensed flying” of Unmanned Aerial Vehicle (UAV) have emerged one after another, which poses a grave threat to the security issues of public facilities and sensitive areas. Whether it can timely detect and prevent “unlicensed flying” of UAV has become a social concern. In response to this demand, the transfer learning method is adopted in this paper to conduct twoclassification and detection on UAV images. Image recognition technology based on transfer learning is an effective method to improve recognition accuracy by applying deep learning models to small samples. Different from the large number of training samples required by deep learning, transfer learning transfers the weights of the pre-trained deep neural network, and uses only small sample data to obtain good results in UAV image recognition. First of all, this paper proposes to construct a UAV data set according to different types of UAV shape structures, to perfect the classification and detection effect and the generalization ability of the model. Then, based on the transfer learning method, experimental comparison is made between three classic deep convolutional neural network classification models (Inception V3, ResNet 101 and VGG16) and two classic deep convolutional neural network detection models (Faster RCNN and SSD). Finally, an experimental evaluation is conducted on the collected UAV test data set. Compared with the traditional recognition model, the image classification model based on transfer learning employed in this paper has achieved important improvements in accuracy, recall and precision. Especially in the InceptionV3 model of transfer training, the recall reaches 96.98%. In addition, the image detection model based on transfer learning has achieved good detection results in accuracy, recall and F1-score.","PeriodicalId":355427,"journal":{"name":"2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133824094","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: 4

Challenges and Opportunities of Language Representation Model 语言表征模型的挑战与机遇

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00076

Ziang Zhou, Ziqian Li, Jiahong Lu

引用次数: 0

A Summary of convolution Neural Network Compression and Acceleration Technology 卷积神经网络压缩与加速技术综述

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00065

Bingzhen Li, Wenzhi Jiang, Jiaojiao Gu, Ke Liu

引用次数: 0

Temperature Compensation and Amplitude Prediction in Ultrasonic Measurement Based on BP Neural Network Mode 基于BP神经网络的超声测量温度补偿与振幅预测

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00068

Wanjia Gao, Fei Li, Ran Yang, Wenyi Liu

{"title":"Temperature Compensation and Amplitude Prediction in Ultrasonic Measurement Based on BP Neural Network Mode","authors":"Wanjia Gao, Fei Li, Ran Yang, Wenyi Liu","doi":"10.1109/ICHCI51889.2020.00068","DOIUrl":"https://doi.org/10.1109/ICHCI51889.2020.00068","url":null,"abstract":"In the system that uses ultrasonic to measure the liquid level, the sound velocity of the ultrasonic will be changed due to the difference in temperature, which will affect the reliability of the experimental results. This paper explores the relationship between temperature and sound velocity, and acoustic impedance. Based on that, the temperature effects on the ultrasonic signals are explored. And this paper fits the evaluations to the temperature compensation formula with the ordinary least squares. Then this paper builds a temperature-amplitude prediction model based on the BP neural network using the received ultrasonic echo data. The evaluations show that as the temperature increases, the received echo amplitude decreases. The voltage drops by 10 mV for every 5°C increase in temperature. The measurement accuracy is $pm 1lt C$. Its linear fitting r2 is 0.99326. The amplitude prediction model built by BP neural network has a prediction accuracy R2 of 0.96887. The error between the predicted value and the ground truth is less than 4.09%. The research can effectively predict the amplitude of data collected at different temperatures. It provides an effective temperature compensation reference in the experiments based on ultrasonic.","PeriodicalId":355427,"journal":{"name":"2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129223275","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

Construction technology of large scale knowledge maps in customer service field of Power Grid 电网客户服务领域大比例尺知识地图构建技术

2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) Pub Date : 2020-12-01 DOI: 10.1109/ICHCI51889.2020.00053

Shuangmei Guo, Yun Pan, Wen Zhang, Chao Ma, Y. Wang, Shidong Zhang

引用次数: 0