检索结果-内蒙古大学图书馆

YuNet: A Tiny Millisecond-level Face Detector

Machine Intelligence Research 2023年第5期20卷 656-665页

作者： Wei Wu Hanyang Peng Shiqi Yu Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Pengcheng Laboratory Shenzhen 518066China

Great progress has been made toward accurate face detection in recent ***,the heavy model and expensive computation costs make it difficult to deploy many detectors on mobile and embedded devices where model size and latency are highly *** this paper,we present a millisecond-level anchor-free face detector,YuNet,which is specifically designed for edge *** are several key contributions in improving the efficiency-accuracy ***,we analyse the influential state-of-theart face detectors in recent years and summarize the rules to reduce the size of ***,a lightweight face detector,YuNet,is *** detector contains a tiny and efficient feature extraction backbone and a simplified pyramid feature fusion *** the best of our knowledge,YuNet has the best trade-off between accuracy and *** has only 75856 parameters and is less than 1/5 of other small-size *** addition,a training strategy is presented for the tiny face detector,and it can effectively train models with the same distribution of the training *** proposed YuNet achieves 81.1%mAP(single-scale)on the WIDER FACE validation hard track with a high inference efficiency(Intel i7-12700K:1.6ms per frame at 320×320).Because of its unique advantages,the repository for YuNet and its predecessors has been popular at GitHub and gained more than 11K stars at https://***/ShiqiYu/***:Face detection,object detection,computer version,lightweight,inference efficiency,anchor-free mechanism.

关键词： Face detection object detection computer version lightweight inference efficiency anchor-free mechanism.

来源：评论

学校读者我要写书评

暂无评论

Understanding Container-based Services under Software Aging: Dependability and Performance Views

IEEE Transactions on Sustainable Computing

引用

IEEE Transactions on Sustainable Computing 2024年第3期10卷 562-575页

作者： Bai, Jing Chang, Xiaolin Machida, Fumio Trivedi, Kishor S. Beijing Jiaotong University Beijing Key Laboratory of Security and Privacy in Intelligent Transportation China University of Tsukuba Department of Computer Science Japan Duke University Department of Electrical and Computer Engineering United States

Container technology, as the key enabler behind microservice architectures, is widely applied in Cloud and Edge Computing. A long and continuous running of operating system (OS) hosting container-based services can encounter software aging that leads to performance deterioration and even causes system failures. OS rejuvenation techniques can mitigate the impact of software aging but the rejuvenation trigger interval needs to be carefully determined to reduce the downtime cost due to rejuvenation. This paper proposes a comprehensive semi-Markov-based approach to quantitatively evaluate the effect of OS rejuvenation on the dependability and the performance of a container-based service. In contrast to the existing studies, we neither restrict the distributions of time intervals of events to be exponential nor assume that backup resources are always available. Through the numerical study, we show the optimal container-migration trigger intervals that can maximize the dependability or minimize the performance of a container-based service. © 2016 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Network of Groupwise Separable Convolution and vision Transformer for Hyperspectral Image Classification 3

A Lightweight Network of Groupwise Separable Convolution and...

引用

3rd International Conference on Optics and Machine vision, ICOMV 2024

作者： Zhao, Zhuoyi Xu, Xiang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China The Artificial Intelligence and Computer Vision Laboratory University of Electronic Science and Technology of China Zhongshan Institute Zhongshan China

ISBN: (纸本)9781510680319

Hyperspectral image (HSI) data consists of images with numerous contiguous spectral bands and promotes the extensive applications in the field of remote sensing. Recent approaches based on vision Transformer (ViT) have achieved remarkable performance in HSI classification tasks due to their ability to extract global spatial features and model long-range dependencies. However, ViT has complex network structure, training is challenging and lacks adequate consideration of local spatial and spectral receptive fields in hyperspectral data. To solve the problems above, we propose a lightweight network model known as the Groupwise Separable Convolution and vision Transformer (GSCViT). Firstly, we introduce a parameter-free attention for spectral calibration (SC). Then, we meticulously design a novel convolutional approach named Groupwise Separable Convolution (GSC), which greatly reduce the number of convolutional kernel parameters and effectively capture local spatial-spectral information in HSI data. In addition, we employ Groupwise Separable Multi-Head Self-Attention (GSSA) to replace the traditional Multi-Head Self-Attention (MSA) in ViT, thus can simultaneously attend to local and global spatial features in HSI with lower computational burden. Experiments on two benchmark HSI datasets demonstrate that our GSCViT model achieves excellent accuracy with relatively small training samples and outperforms some existing HSI classification algorithms. © 2024 SPIE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

An efficient Quasi-Affine Transformation Evolutionary algorithm with fixed dimension updating and its application in UAV 3D path planning

引用

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 9755-9781页

作者： Sung, Tien-Wen Zhao, Baohua Zhang, Xin Lee, Chao-Yang Fang, Qingjun Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Computer Science and Mathematics Fujian University of Technology Fuzhou China Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a kind of swarm-based collaborative optimization algorithm that solves the problem of a position deviation in a DE search by using the co-evolution matrix M instead of the cross-control parameter CR in the differential evolution algorithm (DE). However, QUATRE shares some of the same weaknesses as DE, such as premature convergence and search stagnation. Inspired by the artificial bee colony algorithm (ABC), we propose a new QUATRE algorithm to improve these problems that ranks all the individuals and evolves only the poorer half of the population. In an evolving population, individuals of different levels intersect with dimensions of different sizes to improve search efficiency and accuracy. In addition, we establish a better selection framework for the parent generation individuals and select more excellent parent individuals to complete the evolution for the individuals trapped in search stagnation. To verify the performance of the new QUATRE algorithm, we divide the comparison algorithm into three groups, including ABC variant group, DE variant group, and QUATRE variant group, and the CEC2014 test suite is used for the comparison. The experimental results show the new QUATRE algorithm performance is competitive. We also successfully apply the new QUATRE algorithm on the 3D path planning of UAV, and compared with the other famous algorithm performance it is still outstanding, which verifies the algorithm's practicability. © 2024 - IOS Press. All rights reserved.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Understanding and Detecting Inefficient Image Displaying Issues in Android Apps

引用

Journal of computer science & Technology 2024年第2期39卷 434-459页

作者：李文杰马骏蒋炎岩许畅马晓星 State Key Laboratory of Novel Software Technology Nanjing UniversityNanjing 210023China Department of Computer Science and Technology Nanjing UniversityNanjing 210023China

Mobile applications(apps for short)often need to display ***,inefficient image displaying(IID)issues are pervasive in mobile apps,and can severely impact app performance and user *** paper first establishes a descriptive framework for the image displaying procedures of IID *** on the descriptive framework,we conduct an empirical study of 216 real-world IID issues collected from 243 popular open-source Android apps to validate the presence and severity of IID issues,and then shed light on these issues’characteristics to support research on effective issue *** the findings of this study,we propose a static IID issue detection tool TAPIR and evaluate it with 243 real-world Android ***,49 and 64 previously-unknown IID issues in two different versions of 16 apps reported by TAPIR are manually confirmed as true positives,respectively,and 16 previously-unknown IID issues reported by TAPIR have been confirmed by developers and 13 have been ***,we further evaluate the performance impact of these detected IID issues and the performance improvement if they are *** results demonstrate that the IID issues detected by TAPIR indeed cause significant performance degradation,which further show the effectiveness and efficiency of TAPIR.

关键词： Android application(app) inefficient image displaying(IID) performance empirical study static analysis

来源：评论

学校读者我要写书评

暂无评论

Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

引用

computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia Abid Muhammad Rizwan Abdulatif Alabdulatif Abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

来源：评论

学校读者我要写书评

暂无评论

Building Advanced RAG Q&A with Multiple Data Sources Using Langchain: A Multi-Search Agent RAG Application in Ubiquitous Learning 2

Building Advanced RAG Q&A with Multiple Data Sources Using L...

引用

2nd International Conference on Computing and Data Analytics, ICCDA 2024

作者： Guettala, Manel Bourekkache, Samir Kazar, Okba Harous, Saad University of Biskra Linfi Laboratory Department of Computer Science Algeria

ISBN: (纸本)9798331542573

The integration of Large Language Models (LLMs) in Question-Answering (QA) systems has made significant progress, yet they often fail to generate precise answers for queries beyond their training data and hallucinating. To address this, our study develops an advanced Retrieval-Augmented Generation (RAG) pipeline method using the LangChain framework, featuring a decision-making agent that dynamically selects the most effective tools and data sources for accurate and contextually relevant responses. By incorporating multiple data sources and diverse tools, our system mitigates the limitations of traditional LLMs, enhancing their effectiveness in ubiquitous learning environments. Evaluation through various case studies shows significant improvements in accuracy, relevance, and contextual appropriateness. The multi-search agent RAG system efficiently retrieves and synthesizes information, supporting continuous and context-aware learning and enriching the user experience. This research advances AI-based educational technologies, delivering a powerful solution for information retrieval and synthesis, as well as laying the foundations for intelligent question-and-answer systems of the future. © 2024 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

A novel medical image data protection scheme for smart healthcare system

引用

CAAI Transactions on Intelligence Technology 2024年第4期9卷 821-836页

作者： Mujeeb Ur Rehman Arslan Shafique Muhammad Shahbaz Khan Maha Driss Wadii Boulila Yazeed Yasin Ghadi Suresh Babu Changalasetty Majed Alhaisoni Jawad Ahmad School of Computer Science and Informatics Cyber Technology InstituteDe Montfort UniversityLeicesterUK Department of Biomedical Engineering University of GlasgowGlasgowUK School of Computing Engineering and the Built EnvironmentEdinburgh Napier UniversityEdinburghUK Robotics and Internet‐of‐Things Laboratory Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science Al Ain UniversityAl AinUnited Arab Emirates Department of Computer Engineering College of Computer Science King Khalid UniversityAbhaSaudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The Internet of Multimedia Things(IoMT)refers to a network of interconnected multimedia devices that communicate with each other over the ***,smart healthcare has emerged as a significant application of the IoMT,particularly in the context of knowledge‐based learning *** healthcare systems leverage knowledge‐based learning to become more context‐aware,adaptable,and auditable while maintain-ing the ability to learn from historical *** smart healthcare systems,devices capture images,such as X‐rays,Magnetic Resonance *** security and integrity of these images are crucial for the databases used in knowledge‐based learning systems to foster structured decision‐making and enhance the learning abilities of ***,in knowledge‐driven systems,the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel,leading to data trans-mission *** address the security and latency concerns,this paper presents a lightweight medical image encryption scheme utilising bit‐plane decomposition and chaos *** results of the experiment yield entropy,energy,and correlation values of 7.999,0.0156,and 0.0001,*** validates the effectiveness of the encryption system proposed in this paper,which offers high‐quality encryption,a large key space,key sensitivity,and resistance to statistical attacks.

关键词： data analysis medical image processing security

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Feature Selection Based on Fisher Score and SVM-RFE for Microarray Data

Informatica (Slovenia)

引用

Informatica (Slovenia) 2024年第1期48卷 57-68页

作者： Hamla, Hind Ghanem, Khadoudja Laboratory of Modelling and Implementation of Complex System Department of Computer Science University of Abdelhamid Mehri Constantine 2 Constantine Algeria

Microarray data analysis has played a significant role in disease diagnosis and tumor type identification over the last two decades. However, due to the curse of dimensionality issues, microarray data classification remains a challenging task. This issue arises from a situation where the number of features is large, but the number of samples is small. As a result, dimension reduction techniques, specifically feature selection methods, are critical for removing non-informative features and improving cancer classification. This paper presents a Filter-embedded hybrid feature selection method to address the gene selection challenge in microarray data analysis. First, it selects the features with the highest Fisher score to create a candidate subset for the next embedded stage. Second, the proposed method employs support vector machine-recursive feature elimination (SVM-RFE) on the candidate subset to identify the optimal set of features to enhance cancer classification. Extensive experiments were conducted with ten high-dimensional microarray datasets to assess the efficacy of the proposed approach. The results show that the proposed method improves classifier performance significantly regarding classification accuracy, number of selected features, and computational efficiency. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Intelligent optimization of computing task management in an Edge environment 6

Intelligent optimization of computing task management in an ...

引用

6th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2024

作者： Cheriet, Amira Mekhaznia, Tahar Department of Computer Science Laboratory of Mathematics Tebessa12002 Algeria

ISBN: (纸本)9798350350265

The advent of Mobile Edge Computing (MEC) offers significant benefits in terms of reduced latency and improved throughput for distributed applications and services. However, the integration of streaming services in these frameworks faces major challenges, particularly in terms of security, due to computational and processing limitations. In this context where resources are deployed as close as possible to the edge network, guaranteeing streaming security poses serious challenges. The restricted computing capabilities of edge nodes make it difficult to perform complex security tasks while maintaining acceptable performance for real-time streaming. To address these challenges, distributed solutions leveraging Network Functions Virtualization (NFV) present themselves as promising options. In this paper, we aim to propose a distributed management solution leveraging NFV capabilities to improve the management of security task execution for streaming, while preserving overall performance. This solution is based on a process of allocation and orchestration of resources for security policies, using NFV Orchestrator (NFVO) nodes. In the evaluation phase, the proposed solution demonstrates that the NFVO-based allocation model demonstrated better performance compared to priority-based and heuristic allocation models. © 2024 IEEE.

关键词： Mobile edge computing

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：