2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET)最新文献

A Lung Cancer Detection and Recognition Method Combining Convolutional Neural Network and Morphological Features 一种结合卷积神经网络和形态学特征的肺癌检测与识别方法

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906329

Yongmei Zhang, Bin Dai, Minghui Dong, Hao Chen, Mengyang Zhou

{"title":"A Lung Cancer Detection and Recognition Method Combining Convolutional Neural Network and Morphological Features","authors":"Yongmei Zhang, Bin Dai, Minghui Dong, Hao Chen, Mengyang Zhou","doi":"10.1109/CCET55412.2022.9906329","DOIUrl":"https://doi.org/10.1109/CCET55412.2022.9906329","url":null,"abstract":"Lung cancer is the malignant tumor with the highest morbidity and mortality, and it is a great threat to human health. With the increasing refinement of lung cancer images, it provides a lot of useful information for the analysis and identification of lung cancer, and an important help to assist doctors in making accurate diagnosis. A considerable part of lung cancer manifests as nodules in the early stage. Pulmonary nodules are round or irregular lesions in the lungs, about 34% are lung cancers, and the rest are benign lesions. Therefore, the detection of pulmonary nodules is very important for the detection of early lung cancer. In this paper, some Computed Tomography (CT) images of the Lung Image Database Consortium (LIDC) dataset are adopted as training and testing data, data preprocessing is completed by intercepting pixels, normalization and other methods, data enhancement is realized such as rotation and scaling methods, and the pulmonary nodule sample library is expanded. Utilizing the constructed lung nodule sample library, train the Convolutional Neural Network (CNN) model, complete the detection and segmentation of pulmonary nodules, and exact the regions of pulmonary nodules. The size and regularity features of pulmonary nodules are extracted, and lung cancer recognition is realized according to the size and shape of pulmonary nodules. The experiment results show the lung cancer detection and identification method based on convolutional neural network with morphological features has higher accuracy.","PeriodicalId":329327,"journal":{"name":"2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125276416","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: 3

A Mask-Wearing Face Recognition Method Based on Low-Level Features and Deep Residual Networks 基于低层次特征和深度残差网络的戴面具人脸识别方法

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906328

Yongmei Zhang, Chenyang Sun, Mengyang Zhou, Haoxing Chen, Minghui Dong

引用次数: 0

Fault Alarm Communication Scheduling Architecture and Method for Power System 电力系统故障报警通信调度体系结构与方法

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906350

Xiangjv Sun, Wenhao Zhan, Y. Li

引用次数: 0

CCET 2022 Cover Page CCET 2022封面页

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/ccet55412.2022.9906327

引用次数: 0

Multi-modal Graph Attention Network for Video Recommendation 视频推荐的多模态图关注网络

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906399

Huizhi Liu, Chen Li, Lihua Tian

引用次数: 1

A Self-Attentive Interest Retrieval Recommender 一个自关注兴趣检索推荐器

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906367

Min Wu, Chen Li, Lihua Tian

{"title":"A Self-Attentive Interest Retrieval Recommender","authors":"Min Wu, Chen Li, Lihua Tian","doi":"10.1109/CCET55412.2022.9906367","DOIUrl":"https://doi.org/10.1109/CCET55412.2022.9906367","url":null,"abstract":"Thanks to the attention mechanism, self-attention networks (SANs) have been widely used in sequential recommendation. However, most existing SANs approaches still follow an old fashion generating one single embedding as final representation, which constraints model’s capacity. To enrich this kind of representation, sequential recommender uses metadata such as item category to capture user’s multi-interests. But this method will not reach its expectation due to item’s long-tail property. This property will result a large constant of category cannot be effectively activated by the lack of interaction records. Another drawback is that may also lead to over-parameterization caused by the massive categories. Particularly, we propose a Self-Attentive Interest Retrieval network (SAIR) to explore a context-aware representation from user’s behaviors while not fall into over-parameterization. SAIR works in a typical SANs manner, encode the behavior sequence using self-attention, and we propose an interest retrieval module to project the sequences to an interest relevance distribution adaptively. And we leverage an interest-to-interest interaction to generate several context-aware interests embeddings. Then we fuse multi-interest embeddings as final output. Extensive experiments are carried out on three real-world datasets, the results demonstrate that SAIR outperforms other SANs methods and other state-of-the-art algorithms in multiple evaluation metrics.","PeriodicalId":329327,"journal":{"name":"2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121544177","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

Construction of Narrative Text Component Recognition Corpus 叙事文本成分识别语料库的构建

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906339

Feng Zhang, Yingqi Han, Jiong Wang, Jie Liu

引用次数: 0

The Innovation of Financial Digitalization Enhances the Financing Capability of Small and Medium-Sized Enterprises: An Empirical Study 金融数字化创新提升中小企业融资能力的实证研究

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906398

Qiwei Huan, B. Bai, Wenbiao Cai, Yundi Chen

{"title":"The Innovation of Financial Digitalization Enhances the Financing Capability of Small and Medium-Sized Enterprises: An Empirical Study","authors":"Qiwei Huan, B. Bai, Wenbiao Cai, Yundi Chen","doi":"10.1109/CCET55412.2022.9906398","DOIUrl":"https://doi.org/10.1109/CCET55412.2022.9906398","url":null,"abstract":"In recent years, severe financing constraints restrict the development of SMEs (small and medium-sized enterprises) and the use of digital finance can play a greater role in the financing of SMEs. This paper conducts research through the empirical analysis method. Based on the existing research findings, the financing constraints of SMEs show a strong cash-cash flow sensitivity. So this paper build a cash-flow sensitivity model to measure financing constraints and add digital finance data variables to explore the impact of digital finance on SMEs’ financing constraints. Then Stata 15.0 statistical software was used to carry out descriptive statistics, correlation analysis, regression analysis, and robustness test. The results show that there are financing constraints in SMEs, and the financing constraints of SMEs are alleviated after joining the digital finance system, which shows that the financing constraints of SMEs can be effectively improved by the digital finance system, but the ability to innovate and empower needs to be improved. The development of digital finance can cut through the data islands, reduce moral risk, rich financing channels, and financing costs indirectly reduced.","PeriodicalId":329327,"journal":{"name":"2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123231662","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

Improving Aerospace Big Data Infrastructure and Applications with Distributed File System and Massive Parallel Calculation 基于分布式文件系统和大规模并行计算的航空航天大数据基础设施与应用

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906364

Fan Xu, Bin Yin, Ming-Zhu Zhang, Xue Wang

引用次数: 0

Detecting Web Application Injection Attacks Using One-Class SVM 一类SVM检测Web应用注入攻击

2022 IEEE 5th International Conference on Computer and Communication Engineering Technology (CCET) Pub Date : 2022-08-19 DOI: 10.1109/CCET55412.2022.9906382

Luchen Zhou, Tao Lu, X. Hu

引用次数: 0