6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023)最新文献_第2页

An unsupervised transfer method for composited image to real image under dark light conditions 暗光照条件下合成图像到实像的无监督转换方法

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004756

Zhixiong Wang, Wei Chen, Zhenyu Fang, Haoyang Zhang, Liang Xie, Ye Yan, Erwei Yin

{"title":"An unsupervised transfer method for composited image to real image under dark light conditions","authors":"Zhixiong Wang, Wei Chen, Zhenyu Fang, Haoyang Zhang, Liang Xie, Ye Yan, Erwei Yin","doi":"10.1117/12.3004756","DOIUrl":"https://doi.org/10.1117/12.3004756","url":null,"abstract":"Most of the existing hand data collection procedures rely on complex and bulky image acquisition systems, in fact, the data directly acquired by the acquisition systems do not have a realistic context, and the neural network models trained from these data perform not well in real-world situations, especially when people are wearing gloves in scenes with changing illumination. However, to improve the consistency of the image the traditional image fusion methods sacrifice the authenticity of the background and the supervised methods are limited by the data acquisition system which cannot generate high quality fusion image. Therefore, based on an unsupervised generative adversarial network, this paper introduced a generator based on a global attention module and proposed a histogram similarity-based image selection module to filter the input images. Our goal is to decrease the difficulty of the image migration task for the network. The model had been trained using a self-built dataset consisting of composited and real data, including images of hands wearing IMU data gloves and photographs taken in real life with similar backgrounds. Extensive experiments on image segmentation tasks demonstrated the effectiveness of the proposed model, which obtained a precision of 0.88 and a recall of 0.86 with a mean NIMA value of 4.27 compared to other state-of-the-art methods such as UEGAN and DoveNet.","PeriodicalId":143265,"journal":{"name":"6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129350810","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

Tunable photonic crystal based on phase change materials for real-time optical path control 基于相变材料的可调谐光子晶体用于实时光路控制

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004860

Yuying Cui, Dingsam Gao, Yichun Zhang, Lulu Chen, Yishan Sun, Zhiyuan Cheng

引用次数: 0

Research on unexploded grenade target recognition algorithm based on YOLOv5 基于YOLOv5的未爆榴弹目标识别算法研究

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004562

Cheng Miao, Z. Lei, Zhao Kai, Mi Gen

引用次数: 0

Research hotspots and trend analysis of text generation for explainable recommendation based on CiteSpace 基于CiteSpace的可解释推荐文本生成研究热点及趋势分析

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004812

Wenjun Meng, Dawei Xu, Runde Yu

{"title":"Research hotspots and trend analysis of text generation for explainable recommendation based on CiteSpace","authors":"Wenjun Meng, Dawei Xu, Runde Yu","doi":"10.1117/12.3004812","DOIUrl":"https://doi.org/10.1117/12.3004812","url":null,"abstract":"Bibliometric analysis was applied to retrieve the international core journals on the subject of text generation for an explainable recommendation from 2000 to 2022. CiteSpace, a visualization-based analysis tool, was used to analyze the research status and recent development of text generation for explainable recommendations by mapping the co-occurrence of high-frequency keywords and citation bursts. The results show that in the past 22 years, the number of international articles on text generation for an explainable recommendation has been on the rise with more publications especially compared with that in China, calling for further exchange and collaboration among scholars and institutions over the world to facilitate the research progress. “Personalized” recommendation has been exerting its influence in text generation for explainable recommendations, which effectively gain the trust of users, and increase the persuasiveness and satisfaction of the recommendation system by providing recommendations with explainable texts. Text processing in Deep Learning has now been widely used for explainable recommendations and will throw its weight further in the future.","PeriodicalId":143265,"journal":{"name":"6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023)","volume":"8 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120891843","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 structure for extracting features of electrocardiogram signals 一种提取心电图信号特征的结构

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004314

Qingyu Yao, Xuesong Su, Siyuan Li, Gongwen Chen

{"title":"A structure for extracting features of electrocardiogram signals","authors":"Qingyu Yao, Xuesong Su, Siyuan Li, Gongwen Chen","doi":"10.1117/12.3004314","DOIUrl":"https://doi.org/10.1117/12.3004314","url":null,"abstract":"Cardiovascular disease, especially coronary artery disease, is always a threat to human health. Myocardial infarction is a form of coronary artery disease. Cardiologists frequently use electrocardiogram (ECG) to diagnose this condition and ensure the health of their patients. Therefore, studying ECG signal classification can aid doctors in accurately identifying the disease and providing appropriate treatment. We develop structure to extract feature from ECG signals, which achieves excellent performance in classification tasks. A single lead ECG signal typically consists of P, QRS, T, and U waves, which collectively form an ECG signal beat. We utilize R-peak detection technology to obtain ECG signal beats, and extract beat features using a residual network. To avoid the loss of global information, we employ a simple onedimensional convolutional neural network (CNN) to obtain global signal features. The fully connected layer is then used to fuse the features obtained from both beats and global signal features. The classification task is completed based on the fused features. Our designed structure improves performance metrics by at least 2% when compared to the performance of a one-dimensional convolutional neural network and a residual network individually. Additionally, we also introduce the SE block into the residual network, which provides an attention mechanism to effectively suppress unnecessary features and enhance important ones. By comparing the performance of our structure with and without SE block, we prove that SE block can enhance our structure's ability to extract ECG signal characteristics.","PeriodicalId":143265,"journal":{"name":"6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116231964","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

BAMGAN: a KBQA method based GAN and bi-directional attention BAMGAN:基于GAN和双向注意的KBQA方法

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004671

Jiazhi Guo

引用次数: 0

Calculation method of well controlled shale oil reserves based on Monte Carlo principle 基于蒙特卡罗原理的井控页岩油储量计算方法

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3005073

Xueyi Zhang, Y. Li, Yuxue Wang

{"title":"Calculation method of well controlled shale oil reserves based on Monte Carlo principle","authors":"Xueyi Zhang, Y. Li, Yuxue Wang","doi":"10.1117/12.3005073","DOIUrl":"https://doi.org/10.1117/12.3005073","url":null,"abstract":"This paper proposes an improved volume method based on Monte Carlo method to address the issue of low accuracy in calculating single well controlled reserves in shale oil horizontal wells. This method first divides the calculation area into units. Then, the probability distribution function of parameters within each unit is obtained through spatial interpolation method. Finally, the Monte Carlo method and volume method are used to calculate the reserve calculation results for each unit, and the well control reserves in the area are obtained by discretizing and accumulating the calculation results of all units. This paper proposes an interpolation method that integrates XGBoost and spatial semi-variogram to perform spatial interpolation on shale porosity in a certain area. Compare the accuracy of each interpolation method using evaluation indicators such as MAE, MSE, MAPE, etc. After comparison, the spatial XGBoost interpolation method integrating semi variogram has an accuracy improvement of over 15% compared to traditional methods, and an accuracy improvement of over 4% compared to the new machine learning spatial interpolation method. This proves that the method proposed in this paper can effectively improve interpolation accuracy.","PeriodicalId":143265,"journal":{"name":"6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131409979","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

Wireless sensor networks multi-strategy clustering mechanism based on improved sparrow search algorithm 基于改进麻雀搜索算法的无线传感器网络多策略聚类机制

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004696

Jixiang Lin, Zhanfei Ma, Wenli Luo

引用次数: 0

Design principle of FFT algorithm and its dual core application FFT算法的设计原理及其双核应用

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004785

Minghao Gao, Fenghao Zhao, Yujie Wang, Zhipeng Zheng

引用次数: 0

Research on parametric modeling of low-voltage switchgear based on OpenCascade 基于OpenCascade的低压开关柜参数化建模研究

6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023) Pub Date : 2023-08-16 DOI: 10.1117/12.3004570

Zheng Cao, Wenhui Wang, Jiawei Li

引用次数: 0