Conference on Electronic Information Engineering and Data Processing最新文献_第6页

Object detection algorithm based on attention mechanism in foggy weather 基于注意力机制的雾天目标检测算法

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682368

Wanye Gu, Yuecheng Yu, Liming Cai, Jinlong Shi, Yongzheng Li, Shixin Huang

{"title":"Object detection algorithm based on attention mechanism in foggy weather","authors":"Wanye Gu, Yuecheng Yu, Liming Cai, Jinlong Shi, Yongzheng Li, Shixin Huang","doi":"10.1117/12.2682368","DOIUrl":"https://doi.org/10.1117/12.2682368","url":null,"abstract":"In this paper, we propose a foggy weather object detection model based on an attention mechanism, to address the problem of low detection accuracy, missed detection and false detection when general object detection models are applied directly to foggy scenes. Firstly, to enhance the detection network's multi-scale expression ability and sensitivity to the target, a residual module that integrates the attention mechanism replaces the BottleNeck module of the backbone network. This design improves the network's ability to extract features and locate targets at a fine-grained level. Secondly, the CIOU loss function replaces the original loss function, improving the stability of the bounding box regression process. Thirdly, the K-means++ clustering algorithm is used to generate anchors suitable for the dataset in this paper. Furthermore, the object detection dataset in foggy scenes is further enriched based on the atmospheric scattering model. Experimental results indicate that the proposed method's mAP in light fog, medium fog and dense fog scenes is increased by 7.4%, 6.05% and 6.36%, respectively, compared to the original YOLOv5s. This improvement in accuracy significantly reduces the missed detection rate and false detection rate, effectively enhancing object detection performance in foggy weather.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114556073","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

Analysis of domestic LoRa application based on bibliometry 基于文献计量学的国内 LoRa 应用分析

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682515

Dezhi Wang, Qingqing Zhang, Chang Liu

{"title":"Analysis of domestic LoRa application based on bibliometry","authors":"Dezhi Wang, Qingqing Zhang, Chang Liu","doi":"10.1117/12.2682515","DOIUrl":"https://doi.org/10.1117/12.2682515","url":null,"abstract":"This paper proposes to analyze the research and application status of LoRa through bibliometry and the knowledge map generated by CiteSpace, and to clarify its research hotspot and development trend. For methods, the 2000-2022 in the National Knowledge Infrastructure database (CNKI) is used. The Excel was used to generate annual distribution, CiteSpace was used to generate knowledge maps of authors, institutions, keywords, etc., and analyze the research application status and frontier of LoRa. A list of results includes a total of 2209 effective documents were obtained, and the number of articles is the author and universities, close cooperation and small cooperation; the nature of LoRa, low power applications include environmental monitoring, intelligent water meter, etc.; long distance applications include data acquisition, data transmission, wireless communication, wireless transmission, etc.; LoRa is more and more widely used, but not very deep, and does not last long. Based on the analysis results, it is found that the research application of LoRa is becoming more and more extensive. From the transmission of a small amount of data to the monitoring and transmission of a large amount of multidimensional data, it can be reasonably inferred that the application of intelligence is still the next research hotspot, and LoRa will still be the main tool in intelligence.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126211233","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

An IoTService modelling approach with the capability of binding to business processes 具有绑定到业务流程能力的IoTService建模方法

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682269

Jian Hu

引用次数: 0

Evaluation model of metacognitive ability based on multi-channel self-attention and BiGRU 基于多渠道自我注意和BiGRU的元认知能力评价模型

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682295

Yingying Cai, Juan Guo, Huiju Yao, Hailin Gan, Qingqing Huang, Feng Zhang

{"title":"Evaluation model of metacognitive ability based on multi-channel self-attention and BiGRU","authors":"Yingying Cai, Juan Guo, Huiju Yao, Hailin Gan, Qingqing Huang, Feng Zhang","doi":"10.1117/12.2682295","DOIUrl":"https://doi.org/10.1117/12.2682295","url":null,"abstract":"Metacognition is the critical element of personalized online autonomous learning, but it is not easy to observe or obtain. It is difficult to be monitored continuously in the practice of teaching and learning. The existing model of metacognitive ability is still in theoretical research and lacks effective model construction technology to externalize metacognition. The online learning behavior data contains rich metacognitive information. In contrast, the previous methods based on statistical analysis or traditional machine learning cannot fully extract the internal temporal and semantic features implied in the data. This study uses the self-attention mechanism and the recurrent neural network sequence model to deeply explore and analyze learners' online learning behavior and interactive text. A new evaluation model of metacognitive ability is constructed to represent learners' metacognitive ability. The research takes natural online learners' behavior data as the object to carry out experimental verification and analysis. The results show that the model's accuracy in representing metacognitive ability reaches 85.21%, which verifies the model's effectiveness.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131957360","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

Simulation research on the whole process of spaceborne XTI-SAR oceanic eddy detection 星载XTI-SAR海洋涡旋探测全过程仿真研究

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682250

Yuhao Lu, Xiaoqing Wang, Qingsong Wang, Haifeng Huang

{"title":"Simulation research on the whole process of spaceborne XTI-SAR oceanic eddy detection","authors":"Yuhao Lu, Xiaoqing Wang, Qingsong Wang, Haifeng Huang","doi":"10.1117/12.2682250","DOIUrl":"https://doi.org/10.1117/12.2682250","url":null,"abstract":"Oceanic eddy is a highly occurring marine phenomenon in the ocean, characterized by closed circulation. Oceanic eddy can cause changes in Sea Surface Height (SSH) and will make the SSH around the center of the oceanic eddy to be higher or lower than the surrounding area, so the identification of oceanic eddy can be achieved by detecting the change of SSH. Traditionally, radar altimeter is an important means to measure the sea surface height, but its resolution is low, so it can’t effectively detect sub-mesoscale oceanic eddies. With its all-time, all-weather, wide-swath and high-resolution characteristics, Synthetic Aperture Radar (SAR) has become a research hotspot in oceanic eddy remote sensing detection. It uses radar antennas from different angles of view to form a baseline, called interferometric SAR, which can achieve the measurement of SSH. In this paper, a signal level simulation model of oceanic eddy for spaceborne cross-track interferometric SAR(XTI-SAR) is established, and an evaluation method based on ideal interferometric factors is introduced. In the experiments, we analyze the influence on the error of oceanic eddy SSH measurement at different sea states. The results show that the increase of wind speed will increase the height measurement error of oceanic eddy, and the difference of wind direction will cause obvious changes in the height measurement error.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123100636","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 of low-frequency phase meter based on STM32 single chip microcomputer 基于STM32单片机的低频相位计设计

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682335

Chengquan Liang, Junsheng Qin

引用次数: 0

IPDF: directed fuzzer for input parsing program 用于输入解析程序的定向模糊器

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682585

Yubo He, Long Liu

{"title":"IPDF: directed fuzzer for input parsing program","authors":"Yubo He, Long Liu","doi":"10.1117/12.2682585","DOIUrl":"https://doi.org/10.1117/12.2682585","url":null,"abstract":"Directed greybox fuzzing aims to test specific code and has made many advances in several areas. However, most vulnerabilities of input parsing programs are triggered in the particular state of the program, so existing directed greybox fuzzing works face path explosion problem when they fuzz the input parsing program and need more ability to explore the particular state of the program. To address the above problem, we propose a call-relationship-based fitness function. The main idea is to use the function call relationship to guide directed fuzzing before reaching the target. Call-relationship-based fitness function extracts the function calls and call relationship from the program, uses an intra-procedural reachability analysis to get all concerned edges, and constructs the fitness function based on the edges. Based on the above method, we implemented the directed greybox fuzzing IPDF and evaluated it with the mainstream directed greybox fuzzers Beacon and AFLGo on real-world programs. Evaluation of IPDF showed that IPDF found vulnerabilities faster than the state-of-the-art directed greybox fuzzers. The experimental results showed that the speed of MDGF is 3.01 times faster than that of AFLGo and 1.15 times faster than Beacon.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132731911","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

Graph neural network-based light-weight recommendation system 基于图神经网络的轻量级推荐系统

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682297

Lin Sun, Shaohua Kuang, Shujian Chen, Xinlin Li, Baobin Duan

{"title":"Graph neural network-based light-weight recommendation system","authors":"Lin Sun, Shaohua Kuang, Shujian Chen, Xinlin Li, Baobin Duan","doi":"10.1117/12.2682297","DOIUrl":"https://doi.org/10.1117/12.2682297","url":null,"abstract":"The recommendation system aims to obtain valuable information for users and alleviate information overload. Graph Neural Network (GNN) is one the mainstream method of recommendation systems for its powerful capabilities of graph data representation and deep feature extraction. But there are still problems with the efficiency and accuracy of GNNs. Therefore, a High-Efficiency Graph Neural Network (HEGNN) is proposed in this paper to build a lightweight graph recommendation system. HEGNN strengthens the local and global preferences of users with attention blocks. It abandons the feature transformation and nonlinear activation layer of vanilla GNNs. Only the basic components are reserved to improve efficiency. Comprehensive comparative experiments with nine baseline algorithms are carried out on three benchmark datasets which include Amazon-Book Dataset, Yelp2018 Dataset, and Gowalla Dataset. Compared with existing recommendation methods such as NGCF and LightGCN, HEGCN not only achieves the highest score on two evaluation metrics of Normalized Discounted Cumulative Gain and Recall but also requires the least training time.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130778343","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

Maximum current speed distribution of ocean surface currents measured with high frequency surface wave radar during the period of severe tropical storm Lionrock 强热带风暴“狮子石”期间高频表面波雷达测得的海洋表面流最大流速分布

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682395

Zhiben Shen, Yun Wang, Jianwei Wu, H. Deng, Ming Chen

引用次数: 0

Algorithm for polyp segmentation with local encoding and decoding fusion and multi-scale attention 基于局部编解码融合和多尺度关注的息肉分割算法

Conference on Electronic Information Engineering and Data Processing Pub Date : 2023-05-26 DOI: 10.1117/12.2682582

Qi Wu, Changming Zhu

引用次数: 0