检索结果-内蒙古大学图书馆

Optimal Deep Convolutional Neural Network for Vehicle Detection in Remote Sensing Images

computers, Materials & Continua 2023年第2期74卷 3117-3131页

作者： Saeed Masoud Alshahrani Saud S.Alotaibi Shaha Al-Otaibi Mohamed Mousa Anwer Mustafa Hilal Amgad Atta Abdelmageed Abdelwahed Motwakel Mohamed I.Eldesouki Department of Computer Science College of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Object detection(OD)in remote sensing images(RSI)acts as a vital part in numerous civilian and military application areas,like urban planning,geographic information system(GIS),and search and rescue *** recognition from RSIs remained a challenging process because of the difficulty of background data and the redundancy of recognition *** latest advancements in deep learning(DL)approaches permit the design of effectual OD *** study develops an Artificial Ecosystem Optimizer with Deep Convolutional Neural Network for Vehicle Detection(AEODCNN-VD)model on Remote Sensing *** proposed AEODCNN-VD model focuses on the identification of vehicles accurately and *** detect vehicles,the presented AEODCNN-VD model employs single shot detector(SSD)with Inception network as a baseline *** addition,Multiway Feature Pyramid Network(MFPN)is used for handling objects of varying sizes in *** features from the Inception model are passed into theMFPNformultiway andmultiscale feature ***,the fused features are passed into bounding box and class prediction *** enhancing the detection efficiency of the AEODCNN-VD approach,AEO based hyperparameter optimizer is used,which is stimulated by the energy transfer strategies such as production,consumption,and decomposition in an *** performance validation of the presentedmethod on benchmark datasets showed promising performance over recent DL models.

关键词： Object detection remote sensing vehicle detection artificial ecosystem optimizer convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Three-Step Intelligent Pruning for Data Classification in Just-in-Time Software Defect Prediction 7

Three-Step Intelligent Pruning for Data Classification in Ju...

引用

7th International Conference on computer and information Processing technology, ISCIPT 2022

作者： Luo, Nan Ma, Ying Department of Computer and Information Engineering Xiamen University of Technology Xiamen China

Just-in-time software defect prediction technology is a defect prediction method that enables defect prediction of software change levels. The difficulties of learning classifiers from imbalanced data is demonstrated in a variety of real-world applications,especially in this era of big data, which has generated more classification tasks. Researchers have taken many existing JIT-SDP efforts to assume that the features of software releases remain costant over time. However, the researchers did not consider that JIT-SDP may be affected by the gradual evolution of class imbalance. Specifically, class imbalance (that is, the number of changes caused by defects is not adequately represented) has been changing over time, and the number of clean class changes and defect class changes may both increase or decrease, so here In this case, the existing JIT-SDP method becomes inapplicable. Taking these factors into consideration, we propose a new imbalanced classification framework, which aims to achieve data class balance by applying a new three-step smart pruning strategy, i.e., first undersampling the majority class, then undersampling the minority class. Oversampling is performed, since the minority class becomes the majority class after oversampling, as a result, the final stage is to intelligently undersample the minority group that eventually becomes the dominant group. Through these three steps, data balance is achieved before classification. Experiments show that this new framework is very computationally efficient, leading to better performance even under highly imbalanced distributions of clean and defective data. At the same time, our proposed framework can also be easily adapted to most existing learning methods to improve their performance on imbalanced data. © 2022 Copyright for this paper by its authors.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Anonymous and robust biometric authentication scheme for secure social IoT healthcare applications

引用

Journal of engineering and Applied Science 2024年第1期71卷 8页

作者： Arpitha, T. Chouhan, Dharamendra Shreyas, J. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Bengaluru India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India

In the era of rapid technological advancement, the Internet of Things (IoT) has revolutionised healthcare through systems like the Telecare Medicine information System (TMIS), designed to streamline patient-doctor interactions and enhance medical treatment. However, the transmission of sensitive patient data over inherently insecure Internet channels exposes it to a spectrum of security risks. Protecting patient medical privacy and ensuring system reliability necessitate mutual authentication between both patients and medical servers. TMIS relies on robust authentication mechanisms, and combining passwords and smart cards has been a recognised approach for mutual authentication. This research introduces an innovative three-factor authentication technique with perfect forward secrecy by leveraging the power of Elliptic Curve Cryptography (ECC) in tandem with smart cards. Additionally, we have incorporated biometric authentication with a Fuzzy Extractor technology to enhance the security and reliability of the system, setting a new standard for user authentication within the realm of Social IoT healthcare. The use of ECC in the method is justified due to its compact key size and robust security measures, making the solution both efficient and secure. The proposed method safeguards user privacy by permitting registered users to change their passwords without divulging their identity to the server. The Burrows–Abadi–Needham logic (also known as the BAN logic) serves as a proof-of-concept for the proposed scheme’s security. Our system provides privacy protection along with mutual authentication and session key negotiation at a considerably low computation cost and communication cost of up to 71.03% compared to the other four relevant techniques, making it more useful in real-world scenarios. © 2023, The Author(s).

关键词： Smart cards

来源：评论

学校读者我要写书评

暂无评论

Evaluating Public Opinion Through Twitter Sentiment Analysis 2

Evaluating Public Opinion Through Twitter Sentiment Analysis

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： Jadhav, Narendra More, Priyanka Dixit, Akhilesh Sharma, Akshay Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367461

In the digital age, social media platforms like Twitter have become a central forum for public discourse, reflecting diverse opinions on various topics. This paper explores the application of sentiment analysis to Twitter data to extract and quantify these opinions. This work processes and analyzes a large dataset of tweets using machine-learning techniques to identify underlying attitudes and divide them into positive, negative, and neutral categories. The methodology comprises preprocessing such as text normalization and noise removal, sentiment categorization using a model based on Natural Language Processing (NLP) techniques, and data gathering via the Twitter API. The results reveal patterns and trends in public sentiment on key issues, providing insights that can benefit businesses, policymakers, and researchers. This paper discusses the potential real-world applications of this technology in marketing, political science, and public relations. © 2024 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Two-Tier Clustering with Routing Protocol for IoT Assisted WSN

引用

computers, Materials & Continua 2022年第5期71卷 3375-3392页

作者： AArokiaraj Jovith Mahantesh Mathapati M.Sundarrajan N.Gnanasankaran Seifedine Kadry Maytham N.Meqdad Shabnam Mohamed Aslam Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Rajarajeswari College of EngineeringBengaluru560074India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science Thiagarajar CollegeMadurai625019India Department of Applied Data Science Noroff University CollegeKristiansandNorway Al-Mustaqbal University College HillahIraq Department of Information Technology College of Computing and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia

In recent times,Internet of Things(IoT)has become a hot research topic and it aims at interlinking several sensor-enabled devices mainly for data gathering and tracking *** Sensor Network(WSN)is an important component in IoT paradigm since its inception and has become the most preferred platform to deploy several smart city application areas like home automation,smart buildings,intelligent transportation,disaster management,and other such IoT-based *** methods are widely-employed energy efficient techniques with a primary purpose i.e.,to balance the energy among sensor *** and routing processes are considered as Non-Polynomial(NP)hard problems whereas bio-inspired techniques have been employed for a known time to resolve such *** current research paper designs an Energy Efficient Two-Tier Clustering with Multi-hop Routing Protocol(EETTC-MRP)for IoT *** presented EETTC-MRP technique operates on different stages namely,tentative Cluster Head(CH)selection,final CH selection,and *** first stage of the proposed EETTC-MRP technique,a type II fuzzy logic-based tentative CH(T2FL-TCH)selection is ***,Quantum Group Teaching Optimization Algorithm-based Final CH selection(QGTOA-FCH)technique is deployed to derive an optimum group of CHs in the ***,Political Optimizer based Multihop Routing(PO-MHR)technique is also employed to derive an optimal selection of routes between CHs in the *** order to validate the efficacy of EETTC-MRP method,a series of experiments was conducted and the outcomes were examined under distinct *** experimental analysis infers that the proposed EETTC-MRP technique is superior to other methods under different measures.

关键词： Wireless networks internet of things energy efficiency clustering multi-hop routing metaheuristics

来源：评论

学校读者我要写书评

暂无评论

Data Mining Artificial Intelligence Techniques for Prediction of Heart Disorders: A Survey

Data Mining Artificial Intelligence Techniques for Predictio...

引用

2019 International Conference on Vision Towards Emerging Trends in Communication and Networking, ViTECoN 2019

作者： Powar, Amogh Shilvant, Seema Pawar, Varsha Parab, Vishesh Shetgaonkar, Pratiksha Aswale, Shailendra Rayeshwar Institute of Engineering and Information Technology Computer Department Goa India

ISBN: (纸本)9781538693537

Heart is the most critical part of human frame. Any abnormal health situations without delay or circuitously affect the heart and all its elements. Heart disease is one of the important health problems in nowadays time. It accounts to be main motive of death global. Many times, it turns into hard for medical practitioners to expect heart disorder on time as it's miles complicated mission that requires revel in and understanding. The fitness quarter in nowadays time comprise lot of treasured hidden facts which can be used and may prove to be essential in making selections for prediction motive. Data mining is the laptop-based system that's used to analyze huge datasets and then extract significant effects by means of the use of extraordinary synthetic strategies. Data mining gear are expecting destiny traits therefore permitting making understanding driven selections. There are many statistics mining techniques like Decision Tree, Naïve Bayes, Neural Network. This paper proposes to use three of those techniques for predicting the coronary heart ailment. Each of these techniques will be tested in the various parameters and different accuracies will be obtained with the different parameters. The accuracy of every method will then be compared based totally on diverse parameters and finally expect whether or not the man or woman gets the coronary heart sickness or now not, with high-quality accuracy. © 2019 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Lightweight irregular driving behavior detection algorithm based on star operation 5

Lightweight irregular driving behavior detection algorithm b...

引用

5th International Conference on computer Vision and Data Mining, ICCVDM 2024

作者： Liang, Jiaxin Department of Computer and Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781510682863

To address the problems of high memory consumption, heavy computational burden, and difficulty deploying existing detection algorithms on edge devices, a lightweight approach for detecting abnormal driving behavior based on an updated YOLOv8 model has been presented. Firstly, the backbone network is replaced with the StarNet network, which has lower computational and memory access requirements. Second, utilizing an enhanced weighted bidirectional feature pyramid network with C2f blocks enhances the model's capability to capture multi-scale features swiftly. Finally, an asymmetric multi-level compression detection head is introduced to reduce the model size further. The experimental findings demonstrate that the suggested enhanced model achieves a 73.2% reduction in parameters, a 60.9% decrease in computational burden, and a 72.8% reduction in model size while retaining the same accuracy as the original YOLOv8 model. This significantly reduces hardware costs, demonstrating excellent lightweight effects. © 2024 SPIE.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

引用

computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

来源：评论

学校读者我要写书评

暂无评论

GUI test script organization with component abstraction

GUI test script organization with component abstraction

引用

2nd IEEE International Conference on Secure System Integration and Reliability Improvement, SSIRI 2008

作者： Chen, Woei-Kae Shen, Zheng-Wen Chang, Che-Ming Department of Computer Science and Information Engineering National Taipei University of Technology

ISBN: (纸本)9780769532660

GUI (Graphical User Interface) testing plays an important role in ensuring the correctness and reliability of software applications. To perform GUI testing, a test script must be prepared (or generated by tools) so that massive user interactions and verifications can be conducted automatically. Ideally, the actions of a test script should be organized based on the structure of the GUI so that the actions are easier to extend and maintain. Unfortunately, current methodologies and tools fall short in supporting such an organization. This paper proposes an "object-based" approach, called component abstraction, to model the structure of a GUI. A GUI testing modeling language, GTML, is defined and a systematic approach in applying component abstraction is described. We show that a test script written in GTML is more robust and easier to maintain in comparison to an ordinary test script. In addition, we implement a visual environment for the development of GTML scripts so that testers (developers) do not need to write GTML scripts in plain-text language. © 2008 IEEE.

关键词： Visual languages

来源：评论

学校读者我要写书评

暂无评论

A scale-based reduction method for surveillance of massive moving objects on mobile devices 11

A scale-based reduction method for surveillance of massive m...

引用

11th International Conference on Distributed Multimedia Systems, DMS 2005

作者： Liao, Hsien-Chou Chen, Wen-Feng Department of Computer Science and Information Engineering Chaoyang University of Technology Taiwan

ISBN: (纸本)1891706179

Recently, the wireless network and mobile devices is getting popular. It causes that many mobile information services are implemented on such devices. The implementation is concerned with four main resources: storage, computing speed, screen size, and network bandwidth. In this paper, a mobile client for surveillance of massive mobile objects is considered. The locations of objects are retrieved from a server and updated periodically. Such application is suffered from the constraints on screen size and network bandwidth. A scale-based reduction method (SRM) is proposed to overcome the above constraints. Scale is an instinctive way to solve the constraints on screen size. Locations are reduced based on the scale and thus decrease the utilization of network bandwidth. Experiments are designed to evaluate the reduction ratio and transmission ratio of SRM. The results illustrate that SRM is effective for surveillance of massive moving objects on mobile devices. © 2005 by Knowledge Systems Institute Graduate School.

关键词： Bandwidth

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：