检索结果-内蒙古大学图书馆

3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Kozulia, Tatiana Kozulia, Mariia National Technical University 'Kharkiv Polytechnic Institute' Department of Software Engineering and Management Intelligent Technologies Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

Determination of the state 'researched system - environment' in the presence of manmade provision is solved by the proposal of comprehensive methodological support - elements of synergetics for modeling of the considered objects with their systemological presentation, which is the subj ect of research. The purpose is determined by the formation of methodological support complex of the object study logic in the systematic representation of it '(system - environment) - processes of internal and external nature -system state - environment'. According to the goal, the main tasks are to introduce a systematic approach to determining the model representation of the object, the implementation of such a model on the basis of a number of statistical methods to bind their results with the basics of synergetics to obtain environmental assessment (system - environment) and its development. Mathematical methods of modeling with the inclusion of elements of systemology, statistical methods, synergetics are involved in solving the tasks. © 2022 IEEE.

关键词： Statistical methods

来源：评论

学校读者我要写书评

暂无评论

Classification of Network Data with Machine Learning Methods for Intelligent Intrusion Detection Systems 4

Classification of Network Data with Machine Learning Methods...

引用

4th International Conference on Advanced Science and engineering, ICOASE 2022

作者： Baykara, Muhammet Abdulrahman, Awf Alahmed, Ali Shakir Firat University Department of Software Engineering Elazig Turkey Duhok Polytechnic University Department of Public Health Duhok Iraq Duhok Polytechnic University Department of Nursing Duhok Iraq

ISBN: (纸本)9781665472227

In information systems, it has become very important to store personal and institutional information and access it safely and quickly when necessary. To ensure the confidentiality of information against unauthorized access, institutions or organizations must protect their important data securely and take various precautions. Intrusion detection systems (IDS) are among these measures. One of the issues that should be carefully considered while creating an IDS is the dataset to be used. In terms of IDS, a dataset is the data obtained from network packets or log records that contain attack data and are necessary to identify attack patterns during the training and testing stages of the system. In this article, widely used machine learning techniques (decision tree, K-nearest neighbor, and support vector machine algorithms) are used to increase the performance of IDSs. The studies were tested on the NSL-KDD dataset, one of the most used datasets in evaluating IDSs. As a result of the tests, it was seen that the highest accuracy rate was 99.7%, and the lowest accuracy rate was 98.7%. The obtained results have shown that the proposed machine learning methods can be used with high sensitivity and accuracy to develop smart IDSs. © 2022 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Application Research on Identification of Cervical Lesions Based on Random Forest 2

Application Research on Identification of Cervical Lesions B...

引用

2nd IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Yao, Bingying Li, Chao Guangzhou University South China Institute of Software Engineering Guangzhou China Guangdong Industry Polytechnic Guangzhou China

ISBN: (纸本)9781665442763

According to analysis of the shortcomings in the course of the joint inspection of HPV-DNA viral load testing and TCT liquid thin-layer cytology technical, application of computer aided diagnosis (CAD) technology to improve cervical cancer screening accuracy, this paper proposes a cervical lesion recognition based on random forest (RF) model. Through characteristic value of cervical cell image are extracted to form the cervical cells characteristic data sets, and then to do the Bootstrap sampling, using a random sample build a decision tree, a feature subset classification results to vote on the cervical cells, use this model in cervical cancer screening. According to theoretical analysis and experimental data, compared with traditional combined examination, this method improves the performance of cervical lesion identification, and its results have certain competitiveness and advantages. © 2022 IEEE.

关键词： Cytology

来源：评论

学校读者我要写书评

暂无评论

Heterologous Image Matching Based on Salience Region Using Q-test and Kernel Density Estimation 4

Heterologous Image Matching Based on Salience Region Using Q...

引用

4th International Conference on Computer Vision and Pattern Analysis, ICCPA 2024

作者： Zhai, Jinlong Yan, Xiaohu Xu, Yang School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-MacaoGreater Bay Area Shenzhen Polytechnic University Shenzhen518055 China

ISBN: (纸本)9781510682528

To address the matching problem caused by the salience differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region using Q-test and kernel density estimation is proposed in this paper. Firstly, the center pixel point of each sub-region in the image is detected for salience difference with other points in its neighborhood by using the Q-test method. The detected points are defined as Q-points. Secondly, the point with the largest kernel density in all Q-points is calculated by using kernel density estimation function and defined as the M-point. Then, the region size is defined according to the coordinates of M-point, and the salience region is detected. Finally, to comprehensively evaluate the performance of the proposed method, five common types of heterologous images are selected as data sources, including point cloud depth maps, infrared images, electronic navigational maps, synthetic aperture radar images, and night-time light images. Based on the salience regions, comparative experiments are carried out using histogram of absolute phase consistency gradients (HAPCG) and histogram of the orientation of the weighted phase descriptor (HOWP). The results show that the matching performance of the proposed method is better than that of the original algorithm without salience region, especially on the type of electronic navigational map. © 2024 SPIE.

关键词： Radar imaging

来源：评论

学校读者我要写书评

暂无评论

Enhancing Scene Text Recognition by Strengthening Attention Alignment 6

Enhancing Scene Text Recognition by Strengthening Attention ...

引用

6th International Conference on Artificial Intelligence and Big Data, ICAIBD 2023

作者： Qing, Shan Chen, Liangwei Lin, Lin Zhang, Jiake Chengdu Aeronautic Polytechnic School of Electronic and Computer Engineering Chengdu China Peking University School of Software & Microelectronics Beijing China Sichuan University School of Literature and Journalism Chengdu China

ISBN: (纸本)9781665491259

Scene text recognition (STR) refers to recognizing text instance images from natural scenes as text. STR has been a hot area of computer vision because it has various applications. The state-of-the-art methods are under the attention-based encoder-decoder framework. However, most of the attention-based methods usually suffer from the problem of attention drift in many situations. We found that a significant cause of attention drift is that the extracted visual features are insufficient. To alleviate this problem, we propose an attention-tuned model, which strengthens attention alignment by learning better visual features. We first adopt deformable convolution to extract good visual features. Next, a stacked self-attention architecture with intermediate supervision is responsible for refining the representation of visual features. Moreover, spatial position encoding is used to guide attention alignment operation. Extensive experiments on standard benchmarks demonstrate that the proposed model achieves state-of-the-art performance for regular and irregular scene text recognition. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

A Real-Time Hand Sign Language Recognition System for Threatening Situations Using Deep Learning 12

A Real-Time Hand Sign Language Recognition System for Threat...

引用

12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Shwany, Zardasht Abdulaziz Abdulkarim Ismail, Shayda Khudhur Khoshnaw, Karwan Hoshyar Khalid Mustafa, Twana Saeed Karabatak, Murat Othman, Nashwan Adnan Erbil Polytechnic University Physiotherapy Department Erbil Iraq Ministry of Higher Education and Scientific Research Network Department Erbil Iraq Erbil Polytechnic University Department of Information and Communication Technology Engineering Erbil Iraq Firat University Department of Software Elazig Turkey College of Science Knowledge University Department of Computer Science Erbil Iraq Knowledge University Department of Computer Engineering Erbil Iraq Al-Kitab University Department of Computer Engineering Altun Kupri Iraq

ISBN: (纸本)9798350330366

Hand sign language has been done as physical movements in natural languages that humans have used since ancient times, along with letters, words, and spoken language. This paper presents a real-time method to identify threatening signs by criminals during interrogation, which increases their criminal rank and helps to reach conclusions. The proposed method is to install a camera of appropriate quality in front of the offender, record hand gestures in a specific area of the hand, apply some image processing techniques, such as contrast enhancement techniques, to the image to facilitate recognition as input, and then classify the images using a convolutional neural network (CNN) for a specific problem with high specifications for that topic by and using AlexNet. The accuracy of the presented method is more than 94.2% in real-time testing. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

引用

Intelligent Automation & Soft Computing 2023年第7期37卷 1-16页

作者： Jixun Gao Bingyi Hu Jialei Liu Huaichen Wang Quanzhen Huang Yuanyuan Zhao School of Computer Henan University of EngineeringZhengzhou451191China School of Computer Science and Technology Henan Polytechnic UniversityJiaozuo454000China School of Computer Hubei University of Arts and ScienceXiangyang441053China School of Software Engineering Anyang Normal UniversityAnyang455000China School of Computer and Information Engineering Henan Normal UniversityXinxiang453003China The Publicity Department Zhengzhou University of TechnologyZhengzhou450044China

Mobile Edge Computing(MEC)is proposed to solve the needs of Inter-net of Things(IoT)users for high resource utilization,high reliability and low latency of service ***,the backup virtual machine is idle when its primary virtual machine is running normally,which will waste *** the backup virtual machine under the above circumstances can effectively improve resource ***,these virtual machines are deployed into slots randomly,and then some tasks with cooperative relationship are off-loaded to virtual machines for *** deployment locations have different resource utilization and average service response *** want toﬁnd a balanced solution that minimizes the average service response time of the IoT application while maximizing resource *** this paper,we propose a task scheduler and exploit a Task Deployment Algorithm(TDA)to obtain an optimal virtual machine deployment ***,the simulation results show that the TDA can signiﬁcantly increase the resource utilization of the system,while redu-cing the average service response time of the application by comparing TDA with the other two classical *** experimental results conﬁrm that the perfor-mance of TDA is better than that of other two methods.

关键词： Mobile edge computing overbooking resource utilization service response time task deployment algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of Neural Networks for Network Traffic Monitoring and Analysis 8

Application of Neural Networks for Network Traffic Monitorin...

引用

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Kushnerov, Oleksandr Murr, Pierre Herasymov, Serhii Milevskyi, Stanislav Melnyk, Marharyta Golovashych, Sergii Sumy State University Department of Economic Cybernetics Sumy Ukraine International University of Science and Technology in Kuwait Computer Engineering Department Kuwait Kuwait 'Kharkiv polytechnic institute' Cybersecurity department National Technical University Kharkiv Ukraine Set University Department of Cyber Security and information protection Kyiv Ukraine National Technical University 'Kharkiv polytechnic institute' Department of Software Engineering and Management Intelligent Technologies Kharkiv Ukraine

ISBN: (纸本)9798350354423

Monitoring and analyzing network traffic are critically important tasks in the context of increasing cyber threats. Traditional data processing methods often struggle to handle the large volumes and complexity of modern network traffic, necessitating the use of advanced technologies such as neural networks and machine learning. This article demonstrates the application of neural networks for monitoring and analyzing network traffic, highlighting their ability to learn from large datasets to detect complex patterns and anomalies. Using TensorFlow, we developed a neural network model based on an autoencoder that effectively identifies and classifies anomalies in network traffic. The model's effectiveness was validated using a synthetic dataset from Kaggle, showing high accuracy on both training and testing data. Our approach significantly improves the efficiency and accuracy of threat detection compared to traditional methods, making it a valuable tool for enhancing cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

Fast Distributed Polynomial Multiplication Algorithm for Lattice-based Cryptographic Decryption In Blockchain Systems 22

Fast Distributed Polynomial Multiplication Algorithm for Lat...

引用

22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Zhao, Hongjian Tao, Yunting Kong, Fanyu Zhang, Guoyan Zhang, Hanlin Yu, Jia Shandong University School of Software Jinan China Binzhou Polytechnic College of Information Engineering Binzhou China Shandong University Shandong Sansec Information Technology Co. Ltd School of Software Jinan China Shandong University School of Cyber Science and Technology Qingdao China Qingdao University College of Computer Science and Technology Qingdao China

ISBN: (纸本)9798331509712

Lattice-based Post-Quantum Cryptography (PQC) can effectively resist the quantum threat to blockchain's underlying cryptographic algorithms. Blockchain node decryption is one of the most commonly used cryptographic computations in blockchain systems, and polynomial multiplication, a time-consuming operation for decryption, is one of the factors limiting blockchain efficiency. This paper proposes a novel distributed computing algorithm for polynomial multiplication, applicable in blockchain decryption. By splitting polynomials into lower-degree terms and delegating tasks to distributed nodes, our approach reduces computation time. A novel verification strategy based on the Karatsuba algorithm ensures result accuracy. The experimental results demonstrate that our proposed scheme improves the execution efficiency of NTT and INTT operations by approximately 47.8% and 52.4%, and reduces Kyber decryption time by up to 23.5%. © 2024 IEEE.

关键词： Encryption algorithms

来源：评论

学校读者我要写书评

暂无评论

3D Gaze Estimation via Binocular Disparity and Feature Refinement 10

3D Gaze Estimation via Binocular Disparity and Feature Refin...

引用

10th International Conference on Big Data Computing and Communications, BIGCOM 2024

作者： Wang, Chengxin Chen, Qiuxia Tian, Ying Yang, Jinfeng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic Shenzhen China

ISBN: (纸本)9798331509538

The eyes are the windows to the soul and are crucial for studying human behavior. Therefore, gaze estimation has attracted much attention in the field of computer vision. In recent years, convolutional neural networks have driven significant progress in gaze estimation research. Despite the remarkable achievements of gaze technology based on full-face images, the inability to obtain full-face images in specific scenarios makes research based on eye images particularly important. This paper proposes a three-dimensional gaze estimation model that takes binocular images as input, using VGG16 as the backbone network for feature extraction. To enhance the feature extraction capability, we have embedded channel attention and spatial attention mechanisms. Meanwhile, to improve the stability of gaze estimation, we classify real gaze angles. First, we perform a preliminary screening of gaze direction through a classification task, and then perform linear regression with the true angle. Finally, we optimize gaze features using binocular vision differences to finetune the gaze estimator. Experiments have shown that our method performs well on three public datasets. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：