2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)最新文献_第3页

Information-Cycle Dual Contractive Learning with Regularization for Unsupervised Image-to-Image Translation 无监督图像到图像翻译的正则化信息循环双收缩学习

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00047

Xin Sun, Zhuang Yin, Siqi Zhang

{"title":"Information-Cycle Dual Contractive Learning with Regularization for Unsupervised Image-to-Image Translation","authors":"Xin Sun, Zhuang Yin, Siqi Zhang","doi":"10.1109/ISAIEE57420.2022.00047","DOIUrl":"https://doi.org/10.1109/ISAIEE57420.2022.00047","url":null,"abstract":"In the tasks of image-to-image translation, we aim to add the appearance features of the target domain on the basis of retaining the structural features of the input image. Contrastive learning methods are gradually applied to image translation tasks. Despite the previous progress in image translation models, it remains challenging to employ an efficient learning setting by capturing image features from multiple perspectives to build mappings. In this paper, we propose a novel method based on information-cycle dual contrastive learning with regularization (ICDCLGAN-R) to improve the overall quality and visual observability which mainly consists of three components: dual-domain GAN, contrastive regularization (CR) and information cycle. Specifically, dual-domain GAN contributes to learning cross-domain image mappings and capturing the domain gap more efficiently by maximizing mutual information between corresponding patches of input and output. Simultaneously, CR utilizes two images from one domain (one real image and one generated image) and one generated image belonging to another domain as positive, anchor and negative, respectively, aiming to pull positive pairs in some metric space and push apart the representation between negative pairs. CR compares multi-source image features meanwhile enhancing information reusability. Besides, we put generated images into dual-domain GAN ulteriorly to perform additional iteration. It reinforces and verifies reconfigurability between images from different domains. In our experiments, we demonstrate that our method improves the quality of generated images and utilizes image features more efficiently.","PeriodicalId":345703,"journal":{"name":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133218046","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

Application of Artificial Intelligence in the Development of Media Integration under the Background of Smart Media 智能媒体背景下人工智能在媒体融合发展中的应用

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00081

Jin Wei, Ran Wang

引用次数: 0

Facial Expression Recognition and the Application of Supervised Contrastive Learning 面部表情识别及其监督对比学习的应用

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00126

Chenxin Yi

引用次数: 0

Research and Development of a Portable Ultrasonic Device for Detecting Urine Volume 便携式尿量超声检测装置的研究与开发

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00112

Kaixuan Sun, Kai Zhao, Sheng Fan, Haobo Zhang, Yunfei Gao, Xiaolin Song, Yu Song, Dong Li

引用次数: 0

Research on Data Transmission Simulation System Based on Computer 3D Simulation Technology 基于计算机三维仿真技术的数据传输仿真系统研究

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00029

Qi Zhang, Xinghua Li

引用次数: 0

Brain Tumor Prediction with LSTM Method LSTM方法预测脑肿瘤

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00010

Zhengbin Chen

{"title":"Brain Tumor Prediction with LSTM Method","authors":"Zhengbin Chen","doi":"10.1109/ISAIEE57420.2022.00010","DOIUrl":"https://doi.org/10.1109/ISAIEE57420.2022.00010","url":null,"abstract":"The second most prevalent illness in the world, brain tumors cause one-sixth of deaths. This paper aims to provide some guidance for people's healthy life by comparing different brain cancer prediction models and to provide a numerical basis for the targeted use of medical financial resources by predicting the incidence and mortality of cancer in the next few years. Primary data on lifestyle habits and cancer incidence from CDC and American Cancer Society, 1990–2017 were used for analysis. To ensure the quality of data sources, this paper first formats conversion and duplicate data elimination, and uses filters the data to obtain the statistical values required for data analysis. Then, the paper selects the cubic spline interpolation technique with good smoothing performance and suitable for the obtained data source to expand the original data and converts the annual data into monthly data. Finally, LSTM and CNN are used to analyze them and then compare their accuracies. The experiment proves that the smallest CNN is the mean square error and mean absolute percentage error of the LSTM model, and R2 (R-square, correlation coefficient) is closest to 1. Therefore, the LSTM model is more suitable for predicting brain tumors.","PeriodicalId":345703,"journal":{"name":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114323566","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 the Planning Method of Traffic Lags Based on Adaptive Ant Colony Algorithms 基于自适应蚁群算法的交通滞后规划方法研究

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00064

Haijian Fu, Shao Hui

引用次数: 0

Design and Implementation of Sports Meeting Intelligent Information Management System Platform Based on Web 基于Web的运动会智能信息管理系统平台的设计与实现

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00055

Wen Ji, Jinghang Cui

引用次数: 0

Time and Space Aggregation Recommendation Model Based on Synthetic Negative Samples 基于合成负样本的时空聚合推荐模型

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00070

Yang Xingyao, Liang Haowen, Yu Jiong, Li Ziyang, Li Chenyu, Zhang Jun

{"title":"Time and Space Aggregation Recommendation Model Based on Synthetic Negative Samples","authors":"Yang Xingyao, Liang Haowen, Yu Jiong, Li Ziyang, Li Chenyu, Zhang Jun","doi":"10.1109/ISAIEE57420.2022.00070","DOIUrl":"https://doi.org/10.1109/ISAIEE57420.2022.00070","url":null,"abstract":"Currently, the recommendation model of the neural network is usually based on space aggregation neighborhood embedded, focusing on gathering information from the perspective of spatial structure information to learn the characteristics of user projects. The negative sampling method is difficult to balance positive and negative samples. In response to the above issues, this article proposes a time-space aggregation recommendation model based on synthetic negative samples. The model uses the multi-header attention mechanism to capture the chronological order of the neighborhood through the multi-header attention mechanism through interactive sequence diagram and sample mixed negative sampling strategies. A mixed sampling of different layers of pooling, thus synthesizing high-quality negative samples so that the model can better learn the boundary between positive and negative instances. Experiments show that the model fully captures users' dynamic interests, enhances the extraction effect of timing characteristics, and alleviates the problem of imbalance of positive and negative samples. And this model can be naturally inserted into the recommendation model of the neural network, which is universal.","PeriodicalId":345703,"journal":{"name":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115155777","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 and implementation of a web application vulnerability detection system 一个web应用漏洞检测系统的设计与实现

2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) Pub Date : 2022-12-01 DOI: 10.1109/ISAIEE57420.2022.00089

Wang Gaolong, Liao Yongzhen

引用次数: 0