2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)最新文献_第4页

A High Input Impedance Low Noise Analog Front-End Chip for Neural Signal Applications 一种用于神经信号应用的高输入阻抗低噪声模拟前端芯片

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995938

Fan Wu, Yanping Ji, Wensi Wang

引用次数: 0

Energy Efficient Edge Computing for Smart Applications in the Post-Moore Era 后摩尔时代智能应用的节能边缘计算

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/asid56930.2022.9995806

Y. Ha

引用次数: 0

Classification of Analog Circuits Based on Graph Convolution Network 基于图卷积网络的模拟电路分类

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9996007

Zhiwei Zheng, Xiongbo Zhang, Yuefan Wang, Shan He, Chao Huang, Lin Li, Donghui Guo

引用次数: 0

Automatic recognition of fetal facial ultrasound standard planes based on improved YOLOv4 基于改进YOLOv4的胎儿面部超声标准面自动识别

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9995820

Hao Xue, Zhonghua Liu, Weifeng Yu, Peizhong Liu

{"title":"Automatic recognition of fetal facial ultrasound standard planes based on improved YOLOv4","authors":"Hao Xue, Zhonghua Liu, Weifeng Yu, Peizhong Liu","doi":"10.1109/ASID56930.2022.9995820","DOIUrl":"https://doi.org/10.1109/ASID56930.2022.9995820","url":null,"abstract":"Accurate acquisition of standard planes of fetal facial ultrasound is essential for subsequent biometry and disease diagnosis. Foreign scholars have extensively researched algorithms for the automatic acquisition of ultrasound standard planes. We view standard plane identification as a detection task, unlike previous classification studies. This study proposes a lightweight target detection network for identifying fetal facial ultrasound standard planes. Methods: Firstly, the model is based on the YOLOv4 algorithm, and given the storage resource limitations of the ultrasound device, we used a lightweight network (GhostNet) to replace the YOLOv4 backbone feature extraction network (CSPDarkNet53). Results: The experimental results show that the average accuracy of the improved YOLOv4 algorithm is 98.06%. The model size is 42.7 MB, a reduction of 85% compared to the original YOLOv4. It takes only 0.07 seconds to detect an ultrasound image, which can fully meet the real-time clinical requirements. It has high detection speed and accuracy, and the model's size is reduced substantially. The algorithm can assist young ultrasonographers in better acquiring high-quality ultrasound images and, to some extent, can address the limitations of the traditional manual approach to acquiring standard planes.","PeriodicalId":183908,"journal":{"name":"2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID)","volume":"556 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127074999","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

Automated DDoS Attack Mitigation for Software Defined Network 软件定义网络的自动DDoS攻击缓解

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9996013

Danni Wang, Sizhao Li

引用次数: 0

UART Controller with FIFO Buffer Function Based on APB Bus 基于APB总线的具有FIFO缓冲功能的UART控制器

2022 IEEE 16th International Conference on Anti-counterfeiting, Security, and Identification (ASID) Pub Date : 2022-12-02 DOI: 10.1109/ASID56930.2022.9996035

Jiajing Li, Lixin Yang, Xi Feng, Y. Xing, Zhijie Chen, Peiyuan Wan

引用次数: 1