International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021)最新文献

Few-shot sketch recognition for plotting system 绘图系统的少镜头素描识别

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2624686

Zelin Yuan

{"title":"Few-shot sketch recognition for plotting system","authors":"Zelin Yuan","doi":"10.1117/12.2624686","DOIUrl":"https://doi.org/10.1117/12.2624686","url":null,"abstract":"Plotting system refers to a software system that can draw a series of vector symbols, typesetting, saving, reading and so on. The traditional plotting system uses key and mouse operation to draw. With the development of electronic equipment touch screen in recent years, the traditional menu selection is not convenient enough, but the way of using hand-painted sketch and recognized by the system is more natural and fast. Traditional image recognition methods need huge amount of data for training, but the vector symbol set in the plotting system is not a common symbol set, so it is difficult to obtain a large amount of data. Therefore, this paper proposes a β-TCVAE-Attention hand-drawn plot recognition method which can obtain better recognition accuracy in the case of small samples. The model first uses the Image dataset to pre-train βTCVAE, and then uses the small sample data of the plot sketch to input the β-TCVAE encoder to obtain the sketch features. After the sketch features are enhanced with the attention module, they are input into the Softmax classifier based on cosine similarity. The neural network is fine-tuned according to the classification results of the classifier. Finally, when using network prediction, input the support set and query graph into the network for classification. In this paper, a 20-way-5shot plotting data set is collected for experiment, and the experiment proves that the model has certain accuracy.","PeriodicalId":123183,"journal":{"name":"International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117154481","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

Study on the optimal process scheme for the selectivity of C4 olefins based on correlation analysis and linear regression 基于相关分析和线性回归的C4烯烃选择性最佳工艺方案研究

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2625429

Shuo Qiu, Ying He, Yaru Chen

引用次数: 0

Design of the interactive art design teaching system with computer network 基于计算机网络的交互式艺术设计教学系统的设计

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2624881

Sihua Huang

引用次数: 0

Research on intelligent spectrum monitoring based on power transformer 基于电力变压器的智能频谱监测研究

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2624880

Haiping Zhang, Minghua Jiang, Jianwei Xu, Jing Wang, Ke Liu

引用次数: 0

Fully content-based IMDb movie recommendation engine with Pearson similarity 完全基于内容的IMDb电影推荐引擎，具有Pearson相似度

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2624930

Chutian Wei, Xinyu Chen, Z. Tang, Wen Cheng

引用次数: 1

Front Matter: Volume 12085 封面:卷12085

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2625634

引用次数: 0

Research progress on preparation methods and photoelectric properties of perovskite solar cell 钙钛矿太阳能电池制备方法及光电性能研究进展

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2625439

Yixuan Li

引用次数: 0

Extraction of the city impervious surface and analysis of the heat island effect based on the multi-source and multi-temporal remote sensing image 基于多源多时相遥感影像的城市不透水面提取及热岛效应分析

International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021) Pub Date : 2021-12-06 DOI: 10.1117/12.2625431

Zongze He, Zhiyuan Hu, Fangtai Hu

{"title":"Extraction of the city impervious surface and analysis of the heat island effect based on the multi-source and multi-temporal remote sensing image","authors":"Zongze He, Zhiyuan Hu, Fangtai Hu","doi":"10.1117/12.2625431","DOIUrl":"https://doi.org/10.1117/12.2625431","url":null,"abstract":"Using remote sensing technology to extract urban impervious surface information has a wide range and high efficiency and plays an essential role in monitoring urban expansion and urban ecological environment change. Generally speaking, if a place is an impervious surface, its surface temperature would be higher. The traditional impervious surface information extraction is based on a single data source and a single-phase remote sensing image, and the error of the extraction results is large. Based on the multi-temporal Sentinel-2 remote sensing image and LJ1-01 nighttime light data in 2018, the impervious surface information was extracted in the main urban area of Qingdao. Combined with the surface temperature retrieved from Landsat OLI/TIRS data, the spatial relationship between the urban heat island effect and impervious surface coverage was analyzed. The results show that multi-temporal and multi-source data can accurately extract urban impervious surface information, and some regions between impervious surface coverage and urban heat island effect cannot show spatial correlation.","PeriodicalId":123183,"journal":{"name":"International Conference on Green Communication, Network, and Internet of Things (GCNIoT 2021)","volume":"505 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134285464","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