2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC)最新文献

Classification for Tomato Disease with Imbalanced Samples Based on TD-MobileNetV2 基于TD-MobileNetV2的番茄不平衡病害分类

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00014

Dasen Li, Zhendong Yin, Zhilu Wu, Qingzhi Liu

引用次数: 3

Constant False Alarm OMP Algorithm Based on Sparse ISAR Imaging of Stationary Aircraft Target 基于静止飞机目标稀疏ISAR成像的恒虚警OMP算法

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00010

Zhanfeng Zhao, Y. Gong, Xiao-Yan Wang

{"title":"Constant False Alarm OMP Algorithm Based on Sparse ISAR Imaging of Stationary Aircraft Target","authors":"Zhanfeng Zhao, Y. Gong, Xiao-Yan Wang","doi":"10.1109/ICISPC53419.2021.00010","DOIUrl":"https://doi.org/10.1109/ICISPC53419.2021.00010","url":null,"abstract":"Compressive Sensing (CS) is a widely used theory which indicates that a signal satisfies sparsity can be reconstructed below Nyquist sampling rate. ISAR imaging usually requires large amounts of data and long periods of observation to ensure high resolution. Through CS theory, the original signal of ISAR can be recovered under a small amount of observed data, reducing the requirement of data volume and the impact of data missing. Greedy algorithms are extensively used as one kind of CS algorithms because it’s more rapidly to find a solution. Orthogonal matching pursuit (OMP) algorithm is the typical algorithm in greedy algorithms. However, CS algorithms usually need more computational time with little data while conventional algorithms. Reducing the computational time is one research direction of CS. In this paper, a Constant False Alarm OMP (CFAR-OMP) algorithm is proposed which simplifies the iteration times. By setting the detection threshold through CFAR, the proposed algorithm only selects atoms in a single cyclic step, effectively reducing the calculation time on the premise of guaranteeing the reconstruction performance. The performance of the proposed algorithm is verified by the comparison of simulation and reconstruction with common thresholds. Finally, through the sparse ISAR imaging experiment of stationary aircraft target, the effectiveness of the proposed algorithm is proved from the simulation and measured data.","PeriodicalId":433072,"journal":{"name":"2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127773682","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

Internet Protocol Version 6 Migration Internet协议版本6迁移

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00022

ZiRui Li, Jikai Qiu

{"title":"Internet Protocol Version 6 Migration","authors":"ZiRui Li, Jikai Qiu","doi":"10.1109/ICISPC53419.2021.00022","DOIUrl":"https://doi.org/10.1109/ICISPC53419.2021.00022","url":null,"abstract":"With the rapid development of the Internet, the continuous increase of Internet users and the increasing demand for Internet applications, IPv4 (Internet Protocol Version 4), the mainstream technology of Internet communication, is facing more and more bottlenecks in reality. Although the current IPV4 network is still Occupying a leading position, some of its limitations have been widely concerned. The International Organization for Standardization---Internet Engineering Task Force (IFTF) has started the research and development of the next-generation Internet protocol Ipgn since the early 1990s. In the mid-1990s, the sixth version of the Internet Protocol-IPv6 was launched. As an upgrade of IPV4, due to the influence of technology and financial resources, IPv6 will not completely replace IPv4 in the short term, and the two will experience a transition (coexistence)-replacing such a long-term process. Therefore, the current research on migration technology from IPV4 to IPv6 has positive practical significance. This paper firstly analyzes the limitations of IPv4 protocol and then discusses the improvements and advantages of IPv6 protocol. Finally, the paper comes to the conclusion that IPv4 and IPv6 will coexist for a long time after summarizing and analyzing the migration from IPv4 to IPv6.","PeriodicalId":433072,"journal":{"name":"2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC)","volume":"294 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114014538","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

[Copyright notice] (版权)

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/icispc53419.2021.00003

引用次数: 0

Detecting Falling Rocks by Estimating Excavation Points Using Laser Pointer 利用激光笔估算开挖点探测落石

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00008

Rei Kobayashi, Yoshihiro Sato, Masaya Miura, Masahito Maemura, Yuto Osada, Yue Bao

引用次数: 0

Joint Robust Transmit and Receive Beamforming Based on Probability Constraint 基于概率约束的联合鲁棒收发波束形成

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00018

Haoran Li, Jun Geng, Junhao Xie

引用次数: 0

Lung Nodule Classification of CT Images Based on the Deep Learning Algorithms 基于深度学习算法的CT图像肺结节分类

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00013

Hassan Mkindu, Longwen Wu, Yaqin Zhao, Liang Zhao

{"title":"Lung Nodule Classification of CT Images Based on the Deep Learning Algorithms","authors":"Hassan Mkindu, Longwen Wu, Yaqin Zhao, Liang Zhao","doi":"10.1109/ICISPC53419.2021.00013","DOIUrl":"https://doi.org/10.1109/ICISPC53419.2021.00013","url":null,"abstract":"Early diagnosis and treatment of lung cancer patients can help to reduce a lung cancer mortality rate that contributes to more than 11.6% of the total cancer-associated deaths. Usually, for patients' diagnosis, Computed Tomography (CT) images are manually diagnosed by radiologists, which is a huge burden to them and sometimes leads to inaccuracy. Therefore, an automated computer-aided diagnosis (CAD) system that can assist radiologists in decision-making is preferable to speed up patients' diagnosis and overcome inaccuracy. This study aims to develop an automated CAD system algorithm that uses a deep Convolutional Neural Network (CNN) for in-depth feature extraction to classify benign and malignant lung nodules from a chest CT scan. The CSPNet and PANet modules are used to combine with the ResNet model for CT scan feature extraction. Due to the multidimensional (3D) nature of CT scans, we propose to use 3D convolutional kernels. We validated the proposed network on CT scan from The Lung Nodule Analysis 2016 (LUNA16) public dataset, which comprises of 888 CT scans. Experimental results show that the proposed algorithm gives a specificity, sensitivity, accuracy, and AUC of 98.98%, 94.42%, 97.09%, and 0.995, respectively. In addition, the results of our design show competitiveness compared to other studies.","PeriodicalId":433072,"journal":{"name":"2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130043036","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: 1

Explainable Sentence-Level Sentiment Analysis for Amazon Product Reviews 亚马逊产品评论的可解释句子级情感分析

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00024

Xuechun Li, Xueyao Sun, Zewei Xu, Yifan Zhou

引用次数: 2

Finger Movement Recognition for Virtual Keyboard Based on sEMG 基于表面肌电信号的虚拟键盘手指运动识别

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00016

Longfei Li, Xuanyu An, Danlei Geng, Shiyi Qin, Sheng Shen

{"title":"Finger Movement Recognition for Virtual Keyboard Based on sEMG","authors":"Longfei Li, Xuanyu An, Danlei Geng, Shiyi Qin, Sheng Shen","doi":"10.1109/ICISPC53419.2021.00016","DOIUrl":"https://doi.org/10.1109/ICISPC53419.2021.00016","url":null,"abstract":"Disabled forelimb has been a main obstacle for people to communicate with computer by keyboard. To achieve the interface with computer, most of them have to use voice commands to interact with it. But this kind of interface has many inconveniences, such as the inability of using it in both noisy and quiet places as well as inadequate provision of commands compared to keyboard. Surface electromyography (sEMG)is a kind of signal that is created when muscles start to contract or the brain produces nerve impulses for muscle contraction. Also the existence of sEMG signals does not depend on the integrity of hands. This project aims to explore the possibility of exploiting sEMG signals to realize that the disabled can interact with the computer through the keyboard. We designed a series of hand movements (sEMG signals) and made them correspond one-to-one with specific strings. By detecting and recognizing the sEMG signals of muscles, the disabled can use the virtual keyboard to interact with the computer normally. In addition, we also designed a signal processing method based on multi-class support vector machine (SVM) with error-correcting output code (ECOC) and label-threshold pre-process. It helps patients in need create their own sEMG signal recognition model. Traditional signal processing method with floating window can accurately identify each action, but it will output the classification results of each action several times, which will cause great inconvenience to the use of the virtual keyboard. This new signal processing method with ECOC and pre-process greatly avoids this problem.","PeriodicalId":433072,"journal":{"name":"2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121980603","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 Massive MIMO Signal Detection Method Based on ZF Method 基于ZF法的海量MIMO信号检测方法

2021 5th International Conference on Imaging, Signal Processing and Communications (ICISPC) Pub Date : 2021-07-01 DOI: 10.1109/ICISPC53419.2021.00021

Yunlong Liu

引用次数: 1