Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications最新文献

A Detection Algorithm of Malicious Domain Based on Deep Learning and Multi-Head Attention Mechanism 基于深度学习和多头注意机制的恶意域检测算法

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098200840091

Siqi Huang, Bo Yan, Dongmei Zhang

引用次数: 1

Evaluation of Attack Effect in Ad Hoc Networks Based on Variable Weight TOPSIS Method 基于变权TOPSIS法的Ad Hoc网络攻击效果评价

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098602130221

Lin Guo, Bin Wu

{"title":"Evaluation of Attack Effect in Ad Hoc Networks Based on Variable Weight TOPSIS Method","authors":"Lin Guo, Bin Wu","doi":"10.5220/0008098602130221","DOIUrl":"https://doi.org/10.5220/0008098602130221","url":null,"abstract":"Evaluation of Attack Effect in Ad Hoc networks is one of the key technologies for Ad Hoc network security applications. In order to solve the traditional attack effect evaluation with the constant weighted summation can’t adjust the relevant weights in time to the change of the attack situation, which causes the limitation and one-sidedness of the judgment. This paper proposes an attack effect evaluation model based on variable weight theory. First, comprehensively considering the relevance of the attack's own complexity and the attack effect, establish an attack effect evaluation indicator system. Then, construct a state variable weight vector expression, so that the weights are adjusted accordingly with the change of the situation. Finally, combined with TOPSIS method, the attack effect evaluation model based on variable weight TOPSIS is constructed. The experimental simulations show that the evaluation results obtained by the model are scientific and reasonable, which makes up for the deviation caused by the decision of the constant weight, and provides a theory and method for the evaluation of the attack effect in Ad Hoc network.","PeriodicalId":415288,"journal":{"name":"Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126808720","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

A Scene Division Method Based on Theme 基于主题的场景划分方法

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098000440048

Fuping Yang, Zhichun Yuan, Xi Cheng

引用次数: 2

Tracking Verification Algorithm Based on Channel Reliability 基于信道可靠性的跟踪验证算法

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008095900590064

Junchang Zhang, Chenyang Xia, Jinjin Wan

{"title":"Tracking Verification Algorithm Based on Channel Reliability","authors":"Junchang Zhang, Chenyang Xia, Jinjin Wan","doi":"10.5220/0008095900590064","DOIUrl":"https://doi.org/10.5220/0008095900590064","url":null,"abstract":"For most algorithms, the problem of Tracking target performance degradation in the case of fast moving, illumination changes, target deformation, occlusion, out-of-plane rotation, low-resolution images, etc. This paper proposes a tracking verification algorithm based on channel reliability. The tracker part of the algorithm is tracked by the method of correlation filter based on channel reliability. By calculating the reliability weight of each feature channel of the input correlation filter, and multiplying the weight by the response of the corresponding channel to obtain the final response, so that the target positioning will be more accurate. The validator part uses the Siamese dual input network in the deep learning convolutional neural network. Every few frames, the verifier will verify the results of the tracker part of the algorithm. If the reliability is verified, the tracking result will not be modified. Otherwise, the validator will re-detect the target location and verify the reliability through the Siamese dual-input network. The tracker will regard this location as the new location of our target continues to be tracked, making target tracking more durable and robust. The experimental evaluation of the OTB13 video sequence proves that the proposed algorithm has good adaptability to target fast motion, illumination change, target deformation, occlusion, and out-of-plane rotation, and has good robustness.","PeriodicalId":415288,"journal":{"name":"Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132610598","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 UAV Image Classification Based on Deep Learning 基于深度学习的无人机图像分类研究

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098701480152

Runqi Li, Cen Chen, Mengyao Chen

引用次数: 2

Intelligent Identification and Emissions Estimation of Harmful Gas Based on Background Segregation Algorithm 基于背景分离算法的有害气体智能识别与排放估计

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008095800050009

Li Leyang, Guo Shuaichen, Hao Peifeng

引用次数: 0

Design and Implementation of Modular Honeynet System Based on SDN 基于SDN的模块化蜜网系统的设计与实现

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098102030212

Yan Li, Bin Wu

引用次数: 2

A Deep Auto-Encoder based LightGBM Approach for Network Intrusion Detection System 基于深度自编码器的LightGBM网络入侵检测方法

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 2019-03-15 DOI: 10.5220/0008098401420147

Kun Mo, Jian Li

引用次数: 4

Total Variation and Tight Frame Iteration Regularization Based Image Reconstruction for Short-scanning Few-view Computer Tomography 基于总变分和紧帧迭代正则化的短扫描少视点计算机断层扫描图像重建

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 1900-01-01 DOI: 10.5220/0008096101030110

Runchu Xu

引用次数: 0

Sphere Localization from a Minimal Number of Points in a Single Image 从单个图像中最小数量的点进行球体定位

Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications Pub Date : 1900-01-01 DOI: 10.5220/0008096300650070

Kunfeng Shi, Xuebin Li, Huikun Xu, Hongmei Zhao, Huanlong Zhang

{"title":"Sphere Localization from a Minimal Number of Points in a Single Image","authors":"Kunfeng Shi, Xuebin Li, Huikun Xu, Hongmei Zhao, Huanlong Zhang","doi":"10.5220/0008096300650070","DOIUrl":"https://doi.org/10.5220/0008096300650070","url":null,"abstract":"This paper proposes a new three-point method to locate the spatial sphere center from a single image. In monocular vision system with known intrinsic parameters, the traditional methods of locating the center of a spatial sphere with known radius require fitting its image points to an ellipse from which the sphere center is extracted. The ellipse fitting procedure requires at least five image points whereas the projection ellipse of a sphere essentially is a three-degree-of-freedom problem, which implies that over-parametrization is introduced in ellipse fitting. In this paper, the ellipse is represented with the three coordinates of the sphere center, and then at least three image points on the ellipse are used to construct a set of quadratic equations of the coordinates from which the Gröbner basis method is used to solve for the coordinates. The experimental results show that the three-point method can solve the problem with less than five image points, and when the number of image points increases to five or more, the new method can also improve sphere localization accuracy and have improved robustness.","PeriodicalId":415288,"journal":{"name":"Proceedings of the International Conference on Advances in Computer Technology, Information Science and Communications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116915343","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