检索结果-内蒙古大学图书馆

Dynamic Quantum Federated Learning for UAV-based Autonomous Surveillance

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8158-8170页

作者： Park, Soohyun Son, Seok Bin Jung, Soyi Kim, Joongheon Sookmyung Women's University Division of Computer Science Seoul Korea Republic of Korea University School of Electrical Engineering Seoul Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon16499 Korea Republic of

In recent years, unmanned aerial vehicles (UAVs) have proven their effectiveness in surveillance due to their superior mobility. By utilizing multiple UAVs with collaborated learning, surveillance of a huge area while consuming minimum resources is possible. However, the performance of UAV collaborative learning systems is still severely limited because the number of parameters in a classical NN is generally very large, which is unsuitable for unstable wireless communication. To address this issue, this paper uses a quantum neural network (QNN), which has large computational capabilities and uses fewer parameters to overcome the problems caused by many parameters. However, it is still difficult to send all the parameters of the QNN to the server under poor channel conditions. Therefore, this paper proposes dynamic quantum federated learning (DQFL), a novel framework designed for UAVs employing quantum computing (QC) and federated learning (FL). The proposed DQFL uses a dynamic quantum neural network (DQNN) with a multi-depth circuit and employs dynamic control of the circuit layer to improve the efficiency of local parameter transmission between UAVs in unstable wireless communication environments. Extensive simulations conducted under real-world autonomous surveillance conditions demonstrate the robustness of DQFL to non-iidness, varying signal-to-noise ratios (SNRs), and poor communication channel conditions in the UAV environment. © 1967-2012 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A robust visual information hiding framework based on HVS pixel adaptive alpha blending (HPAAB) technique

引用

Multimedia Tools and Applications 2025年第14期84卷 13959-13982页

作者： Panda, Bishwabara Nayak, Manas Ranjan Mallick, Pradeep Kumar Basu, Abhishek School of Computer Engineering KIIT Deemed to be University Bhubaneswar India Department of ECE RCC Institute of Information Technology Kolkata India

The popularity of the Internet and digital consumer gadgets has fundamentally changed our society and daily lives by making digital data collection, transmission, and storage exceedingly easy and convenient. However, protecting these data and preventing unauthorized changes is an important task. This challenge has arisen in several domains, including copyright protection, content authentication, information concealment, and protected communications. Several academics have developed digital watermarking algorithms to solve this issue, aiming to implant hidden data (a watermark) in digital material to affix a mark on or seal the digital data content. The proposed approach builds a spatial domain image watermarking approach using entropy, a spectral residual pixel-based saliency map, and alpha blending. This method states that the value of entropy improves the concealing capacity. To increase imperceptibility, a spectral residual-based saliency map is used to discover less visible portions of the input images and progressively incorporate more information based on entropy data. Any modifications made other than those detectable regions will be less noticeable to viewers since they result from saliency, which decides which elements of an image are the most visible from a visual perspective. Lastly, utilizing the quality criteria, the mechanism's capability is analyzed for numerous existing frameworks. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

On the Misspecified Cramér-Rao Bound and Elliptically Symmetric Distributions 59

On the Misspecified Cramér-Rao Bound and Elliptically Symme...

引用

59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Richmond, Christ D. Duke University Pratt School of Engineering Department of Electrical and Computer Engineering DurhamNC United States

ISBN: (纸本)9798331513269

Parameter estimation is among the many goals of engineering systems and scientific applications, and parameter bounds have provided significant insights into achievable system performance. These bounds are based on an assumed distribution for the data that may differ from the true data distribution, i.e. often the impacts of model misspecification are inevitable. Thus, researchers have derived Slepian-Bangs-type formulas for elliptically symmetric distributions under model misspecification to explore these effects. The present work continues this exploration by establishing a simple version of the Slepian formula applicable to circular complex compound Gaussian distributed data (a special class of non-Gaussian distributions, also sometimes called Gaussian mixtures), when the data distribution assumed for algorithm development is complex Gaussian. © 2025 IEEE.

关键词： Cramer-Rao bounds

来源：评论

学校读者我要写书评

暂无评论

Soft Computing Paradigms for Load Balancing in Cloud Computing 3rd

Soft Computing Paradigms for Load Balancing in Cloud Computi...

引用

3rd International Conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Ghafir, Shabina Alam, M. Afshar Alankar, Bhavya Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India

ISBN: (纸本)9789819719457

This paper provides a comprehensive comparison of load-balancing algorithms employed in cloud computing, spanning from the earliest to the most recent developments. Emphasizing the significance of load balancing for system performance, resource optimization, and equitable allocation among users, the paper offers insights into various techniques, their effectiveness across workloads, and associated limitations. With an overview of each algorithm, this study caters to practitioners and researchers in the dynamic field of cloud computing, aiming to contribute valuable perspectives for enhanced system efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

An Efficient Approach to Lip-Reading with 3D CNN and Bi-LSTM Fusion Model 5th

An Efficient Approach to Lip-Reading with 3D CNN and Bi-LSTM...

引用

5th International Conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Joshi, Rohit Chandra Juyal, Aayush Jain, Vishal Chaturvedi, Saumya Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida201310 India

ISBN: (纸本)9789819773701

Communication occurs commonly between two or more individuals and often it involves the use of speech. However, under certain circumstances, the use of speech may be restricted causing a hindrance in communication. These circumstances may include noisy environments, people with hearing disability, and corrupt audio in forensic analysis. The alternative to speech in this situation can be to visually analyze the content from the patterns of lip movements to deduce the message. This phenomenon is known as lip-reading. Lip-reading can be intricate using the naked eye for an individual. Artificial Intelligence (AI) has gained recent attention in many fields, with speech recognition being one of them. The use of Machine Learning (ML) and Deep Learning (DL) algorithms, falling under the umbrella of Artificial Intelligence, can help build Automatic Lip-Reading (ALR) systems that can ease the process of lip-reading. This work aims to build an ALR system while obtaining a great performance compared to some of the state-of-the-art methods on the Grid corpus dataset. The proposed model is segregated into two parts: frontend and backend. The front end employs a 3D Convolutional Neural Network (CNN) and the back end uses a Bi-directional Long Short-Term Memory (Bi-LSTM) architecture. The model attained a Word Error Rate (WER) of 0.093, outperforming several baseline models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Early Parkinson's Disease Detection and Classification using Machine Learning and Neutrosophic Sets

引用

Neutrosophic Sets and Systems 2025年 82卷 873-886页

作者： Oudah, Hasan H. Metwaly, Ahmed A. Eassa, Mohamed Abdelhafeez, Ahmed Nagm, Ahmad M. Salama, Ahmed S. College of Arts Department of Journalism Ahl Al Bayt University Karbala Iraq Department of Computer Science Faculty of Computers and Informatics Zagazig University Zagazig44519 Egypt Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Engineering and Electronics Cairo Higher Institute for Engineering Computer Science and Management New Cairo Egypt

Optimizing therapy and rehabilitation for Parkinson's disease (PD) requires early identification and precise evaluation of the illness's course. However, there is disagreement about the best way to use gait analysis to categorize the severity of motor symptoms and identify early-stage Parkinson's disease. The precision of machine learning (ML) models in identifying early and intermediate stages of Parkinson's disease was assessed in this study. Six ML models are used in this study for the prediction of PD. Different metrics are used to evaluate ML models such as accuracy, precision, recall, f1-score, and AUC score. Then we propose a multi-criteria decision-making methodology (MCDM) to evaluate the ML models and select the best one. Two MCDM methods are used such as CRITIC method to compute the criteria weights and the TOPSIS method to rank the alternatives. These methods are used under the bipolar neutrosophic sets (BNSs) to deal with uncertainty information. The results show the support vector machine is the best ML model for the prediction of PD. © 2025, University of New Mexico. All rights reserved.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

Blockchain in Electronic Voting: A Systematic Review of Security, Scalability, and Emerging Technologies 3

Blockchain in Electronic Voting: A Systematic Review of Secu...

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Gupta, Shantanu Tyagi, Neha Amity University Amity School of Engineering & Technology Department of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798331515911

Blockchain technology has emerged as a promising solution for enhancing the security, transparency, and efficiency of electronic voting systems. This review paper presents a comprehensive analysis of recent research papers, examining various cryptographic techniques, consensus mechanisms, and blockchain frameworks designed to address critical issues such as voter anonymity, coercion resistance, and election integrity. The findings are categorized into key themes: security, privacy, scalability, verifiability, and performance, with an emphasis on advanced methods like biometric encryption and quantum key distribution. Emerging trends, including quantum cryptography and decentralized governance, are explored as future avenues for innovation. Despite these advancements, challenges related to governance, user engagement, legal frameworks, and system interoperability persist. The paper concludes by identifying the need for further research into scalability and security improvements, as well as the seamless integration of blockchain solutions with existing electoral infrastructure to enable real-world adoption © 2025 IEEE.

关键词： Anonymity

来源：评论

学校读者我要写书评

暂无评论

Enhanced Cyclone Intensity Estimation Through CNN Analysis of INSAT-3D IR Imagery 12th

Enhanced Cyclone Intensity Estimation Through CNN Analysis o...

引用

12th International Conference on Recent Trends in Computing, ICRTC 2024

作者： Kumar, Divvela Vishnu Sai Arora, Deepak Tiwari, Shivam Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Lucknow Campus Lucknow India Department of Computer Science and Engineering Sharda University Greater Noida India

ISBN: (纸本)9789819788354

Cyclone forecasting using satellite pictures involves anticipating the cyclone’s intensity in advance of its arrival. The results of this study can inform people’s preparations for the cyclone. In order to save lives and reduce damage, cyclone strength forecast is crucial. As a result of the many dangers they pose, these cyclones are among the most expensive natural disasters that have ever occurred. Five separate CNN (Convolutional Neural Network) models are presented by the authors to assess the cyclone’s severity using INSAT-3D infrared pictures. While many methods exist for making such an assessment, the authors’ top model yields an RMSE of 10.02 kts for intensity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Occluded human pose estimation based on limb joint augmentation

引用

Neural Computing and Applications 2025年第3期37卷 1241-1253页

作者： Han, Gangtao Song, Chunxiao Wang, Song Wang, Hao Chen, Enqing Wang, Guanghui School of Electrical and Information Engineering Zhengzhou University Zhengzhou China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China Department of Computer Science Toronto Metropolitan University Toronto Canada

Human pose estimation aims at locating the specific joints of humans from the images or videos. While existing deep learning-based methods have achieved high positioning accuracy, they often struggle with generalization in occlusion scenarios. In this paper, we propose an occluded human pose estimation framework based on limb joint augmentation to enhance the generalization ability of the pose estimation model on the occluded human bodies. Specifically, the occlusion blocks are at first employed to randomly cover the limb joints of the human bodies from the training images, imitating the scene where the objects or other people partially occlude the human body. Trained by the augmented samples, the pose estimation model is encouraged to accurately locate the occluded keypoints based on the visible ones. To further enhance the localization ability of the model, this paper constructs a dynamic structure loss function based on limb graphs to explore the distribution of occluded joints by evaluating the dependence between adjacent joints. Extensive experimental evaluations on two occluded datasets, OCHuman and CrowdPose, demonstrate significant performance improvements without additional computation cost during inference. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Joints (anatomy)

来源：评论

学校读者我要写书评

暂无评论

Optimal control for unreliable manufacturing and remanufacturing system under environmental subsidy and overrun penalty mechanism

引用

IEEE Transactions on engineering Management 2025年 72卷 1983-2002页

作者： Turki, Sadok Jemmali, Mahdi Hidri, Lotfi University of Lorraine Department of Logistic and Maintenance UFR MIM at Metz Metz17 France University of Sharjah Computer Science Department College of Computing and Informatics Sharjah United Arab Emirates King Saud University Industrial Engineering Department College of Engineering Riyadh11421 Saudi Arabia

Because of environmental concerns, remanufacturing has become an integral process for many production companies. Most published papers dealing with manufacturing and remanufacturing systems (MRSs) overlook some industrial features. These include machine unreliability, the distinction between newly manufactured and remanufactured products, and uncertainty about the returned used products (RUPs). As a result, these models do not reflect the reality of industrial systems. This study aims to bridge the gap in research on MRSs by elaborating an optimal and dynamic control of manufacturing, remanufacturing, and recovery of RUPs. The goal is to develop a model based on manufacturing remanufacturing emissions hedging point control policy (MREHP) to adjust the production of new and remanufactured products, and recovery of RUPs according to economic and environmental thresholds. To reduce carbon emissions, a new method is proposed based on the environmental subsidy and overrun penalty mechanism (ESOPM), and that is combined with MREHP to control in parallel the MRS and generated emissions. A robust optimization algorithm is developed to determine the optimal economic and environmental thresholds in MREHP and ESOPM. A comparative study is provided to evaluate our proposed ESOPM in comparison with traditional reduction policies: carbon cap and trade (CCT) and carbon tax regulation (CTR). The obtained results reveal that machines' reliability, rate of RUPs, emissions subsidy, and carbon emissions limit have notable impacts on economic and environmental thresholds. Additionally, results show that the proposed ESOPM performs higher profit than CTR and CCT while reducing emissions when the carbon price is below a certain value. © 1988-2012 IEEE.

关键词： Fabrication

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：