检索结果-内蒙古大学图书馆

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Liu, Zhihang Huang, Qiang Zhu, Yingying College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9781643685489

Composed image retrieval seeks to retrieve a target image that fulfills both modalities based on the user's query, which comprises a modified text and a reference image. Although existing studies introduce novel multi-modal feature fusion techniques at the global or local level, they ignore exploring the cross-level semantic correspondence and recombining the original and target features in the reference image and the modified text, and the problems of modal inconsistency. To address these issues, we propose a CLIP-based Cross-Level Semantic Interaction and Recombination Network (SeIR). Specifically, we first resort the image and text encoders of the CLIP pre-trained model to narrow the modal gap between image and text, and extract both global and local features. We also introduce a cross-modal attention mechanism to screen out original and target features by exploring the semantic correlation between the cross-level image and text features. Subsequently, to alleviate the modal difference between the generated composed query representation and the target image, we utilize an affine transformation technique to recombine the original and target features from the image and text. Extensive experiments on the FashionIQ and CIRR benchmark datasets demonstrate the competitive performance of the proposed SeIR compared to the state-of-the-art methods. © 2024 The Authors.

关键词： Affine transforms

来源：评论

学校读者我要写书评

暂无评论

An object detection approach with residual feature fusion and second-order term attention mechanism

引用

CAAI Transactions on Intelligence Technology 2024年第2期9卷 411-424页

作者： Cuijin Li Zhong Qu Shengye Wang College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqingChina College of Electronic Information Chongqing Institute of EngineeringChongqingChina

Automatically detecting and locating remote occlusion small objects from the images of complex traffic environments is a valuable and challenging *** the boundary box location is not sufficiently accurate and it is difficult to distinguish overlapping and occluded objects,the authors propose a network model with a second-order term attention mechanism and occlusion ***,the backbone network is built on *** a method is designed for the feature extraction network based on an item-wise attention mechanism,which uses the filtered weighted feature vector to replace the original residual fusion and adds a second-order term to reduce the information loss in the process of fusion and accelerate the convergence of the ***,an objected occlusion regression loss function is studied to reduce the problems of missed detections caused by dense *** experimental results demonstrate that the authors’method achieved state-of-the-art performance without reducing the detection *** mAP@.5 of the method is 85.8%on the Foggy_cityscapes dataset and the mAP@.5 of the method is 97.8%on the KITTI dataset.

关键词： artificial intelligence computer vision image processing machine learning neural network object recognition

来源：评论

学校读者我要写书评

暂无评论

Enhancing Skin Disease Diagnosis: Light GBM-DMS Algorithm for Accurate Image Classification

引用

Cognitive Computation 2025年第3期17卷 1-18页

作者： Kalpana, B. Senthilselvi, A. Muruganandam, S. Kumar, S. Vinodh Department of Information Technology RMD Engineering College Tamil Nadu Kavaraipettai India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai India Department of Computer Science and Business Systems Panimalar Engineering College Poonamallee Chennai Tamil Nadu India Department of Computer Science and Engineering Rajalakshmi Engineering College Tamil Nadu Thandalam Chennai India

Globally, skin diseases are emerging as the most common health problem. It initiates depressive disorder, and it also causes physical health distress. It rarely led to skin cancer in extreme cases. Diagnosing skin disease is subjective and time-consuming when it is performed by health experts manually. Hence, automatic skin disease prediction is required by both dermatologists and patients to enhance and accelerate treatment plans. Even though many machine-learning techniques are available to detect skin diseases, the timely prediction and accurate classification of skin lesions are still in demand. Hence, the Discrete Mycorrhizal Search Algorithm is used to optimize the novel LightGBM to meet this objective. Firstly, intrusions like noise elimination and hair removal are performed and then the image resizing takes place by utilizing the preprocessing pipelines. Subsequent to data pre-processing, the prime features are extracted using the convolutional self-attention based L2 regularization, thus minimizing the data complexity. At last, the extracted features are shifted to the final categorization phase which is done by the novel approach for effective classification of skin diseases. Two skin disease classification images, including datasets, the Skin Lesions Dermatoscopic Image dataset and Skin Cancer MNIST HAM10000, are selected to validate the classification performance. Comprehensive analyses are performed with significant measures that showed the proposed model attained better performances of 98.6%, 0.95, and 10.43 s from accuracy, intersection of union, and execution time, respectively. The stability and robustness under different environmental conditions for clinical applications in skin disease detection and classification tasks are analyzed for making decisions in real-time scenarios. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Dermatitis

来源：评论

学校读者我要写书评

暂无评论

Expensive Optimization Based on Evolutionary Multi-Tasking and Hybrid Restart Strategy 13

Expensive Optimization Based on Evolutionary Multi-Tasking a...

引用

13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Zhenyuan Ma, Xiaoliang Zhu, Zexuan Li, Yueyue College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9798350308365

Evolutionary Algorithms (EAs) can not handle expensive optimization problems (EOPs) well due to the limited function evaluations in EOPs. To address this challenge, surrogate-assisted evolutionary algorithms (SAEAs) have been widely used and obtained good performance. With the problem dimension increases, SAEAs encounter some challenges in relatively high complexity on the training time and prediction time. To address this, this article proposes a novel expensive optimization algorithm with evolutionary multi-tasking and hybrid restart strategy (HRS-EMT). In the surrogate model construct, two radial basis function (RBF) models with different kernel functions are trained on all evaluated data to provide diversity and then are solved by a multi-tasking optimizer to a better optimization performance. In the surrogate model management, HRS-EMT combines multiple RBF models into an ensemble RBF (ERBF) model, strategically applied in the initial population pre-selection of surrogate model. Based on the prediction of ERBF surrogate model, HRS-EMT can obtain a better initial population in high dimensions. HRS-EMT is validated on twelve benchmark functions and compared with other state-of-the-art SAEAs. Experimental studies have shown the superior or comparable performance to other popular SAEAs in addressing EOPs. © 2024 IEEE.

关键词： evolutionary multitasking Expensive optimization infill criteria surrogate-assisted optimization

来源：评论

学校读者我要写书评

暂无评论

A privacy and compliance in regulated anonymous payment system based on blockchain

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第8期15卷 3141-3157页

作者： Elfadul, Issameldeen Wu, Lijun Elhabob, Rashad Elkhalil, Ahmed School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan250200 China Faculty of Computer Science and Information Technology Karary University Khartoum Sudan

Decentralized Anonymous Payment Systems (DAP), often known as cryptocurrencies, stand out as some of the most innovative and successful applications on the blockchain. These systems have garnered significant attention in the financial industry due to their highly secure and reliable features. Regrettably, the DAP system can be exploited to fund illegal activities such as drug dealing and terrorism. Therefore, governments are increasingly worried about the illicit use of DAP systems, which poses a critical threat to their security. This paper proposes Privacy and Compliance in Regulated Anonymous Payment System Based on Blockchain (PCRAP), which provides government supervision and enforces regulations over transactions without sacrificing the essential idea of the blockchain, that is, without surrendering transaction privacy or anonymity of the participants. The key characteristic of the proposed scheme is using a ring signature and stealth address to ensure the anonymity of both the sender and receiver of the transaction. Moreover, a Merkle Tree is used to guarantee government supervision and enforce regulations. Our proposed scheme satisfies most of the stringent security requirements and complies with the standards of secure payment systems. Additionally, while our work supports government regulations and supervision, it guarantees unconditional anonymity for users. Furthermore, the performance analysis demonstrates that our suggested scheme still remains applicable and effective even when achieving complete anonymity. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

引用

Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 128-140页

作者： Bing Sun Ruipeng Jing Leijiao Ge Yuan Zeng Shimeng Dong Luyang Hou the School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China State Grid Corporation of China BeijingChina the School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijingChina

The smart distribution network(SDN)is integrat ing increasing distributed generation(DG)and energy storage(ES).Hosting capacity evaluation is important for SDN plan ning with *** and ES are usually invested by users or a third party,and they may form friendly microgrids(MGs)and operate *** centralized dispatching meth od no longer suits for hosting capacity evaluation of SDN.A quick hosting capacity evaluation method based on distributed optimal dispatching is ***,a multi-objective DG hosting capacity evaluation model is established,and the host ing capacity for DG is determined by the optimal DG planning *** steady-state security region method is applied to speed up the solving process of the DG hosting capacity evalua tion ***,the optimal dispatching models are estab lished for MG and SDN respectively to realize the operating *** the distributed dispatching strategy,the dual-side optimal operation of SDN-MGs can be realized by several iterations of power exchange ***,an SDN with four MGs is conducted considering multiple flexible *** shows that the DG hosting capacity of SDN oversteps the sum of the maximum active power demand and the rated branch ***,the annual DG electricity oversteps the maximum active power demand value.

关键词： Smart distribution network(SDN) microgrid hosting capacity multi-objective optimization distributed opti mal dispatching flexible resource

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Side-Channel Attack Detection for Mobile Devices Security in 5G Networks

引用

清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence-inspired comprehensive framework for desertification prediction

International Journal of Cognitive Computing in Engineering

引用

International Journal of Cognitive Computing in engineering 2025年 6卷 462-476页

作者： Alsubai, Shtwai Mosleh, Mogeeb A.A. Al-Hadhrami, Suheer A. Bhatia, Munish College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Alkharj Saudi Arabia Faculty of Engineering & Computing University of Science & Technology Aden Yemen Faculty of Engineering and Information Technology Taiz Univeristy Taiz Yemen Department of Computer Engineering College of Engineering Al Mukalla Hadhramout Yemen Department of Computer Applications National Institute of Technology Kurukshetra India

Desertification greatly affects land deterioration, farming efficiency, economic growth, and health, especially in Gulf nations. Climate change has worsened desertification, making developmental issues in the area even more difficult. This research presents an enhanced framework utilizing the Internet of Things (IoT) for ongoing monitoring, data gathering, and analysis to evaluate desertification patterns. The framework utilizes Bayesian Belief Networks (BBN) to categorize IoT data, while a low-latency processing method on edge computing platforms enables effective detection of desertification trends. The classified data is subsequently analyzed using an Artificial Neural Network (ANN) optimized with a Genetic Algorithm (GA) for forecasting decisions. Using cloud computing infrastructure, the ANN-GA model examines intricate data connections to forecast desertification risk elements. Moreover, the Autoregressive Integrated Moving Average (ARIMA) model is employed to predict desertification over varied time intervals. Experimental simulations illustrate the effectiveness of the suggested framework, attaining enhanced performance in essential metrics: Temporal Delay (103.68 s), Classification Efficacy—Sensitivity (96.44 %), Precision (95.56 %), Specificity (96.97 %), and F-Measure (96.69 %)—Predictive Efficiency—Accuracy (97.76 %) and Root Mean Square Error (RMSE) (1.95 %)—along with Reliability (93.73 %) and Stability (75 %). The results of classification effectiveness and prediction performance emphasize the framework's ability to detect high-risk zones and predict the severity of desertification. This innovative method improves the comprehension of desertification processes and encourages sustainable land management practices, reducing the socio-economic impacts of desertification and bolstering at-risk ecosystems. The results of the study hold considerable importance for enhancing regional efforts in combating desertification, ensuring food security, and formulatin

关键词： Life on land Climate action Desertification Internet of things Artificial neural network

来源：评论

学校读者我要写书评

暂无评论

Short-time maritime target detection based on polarization scattering characteristics

引用

Journal of Systems engineering and Electronics 2024年第1期35卷 55-64页

作者： CHEN Shichao LUO Feng TIAN Min LYU Wanghan College of Computer and Information Engineering(College of Artificial Intelligence) Nanjing Tech UniversityNanjing 211816China Hangzhou Institute of Technology Xidian UniversityHangzhou 311200China

In this paper,a detection method combining Cameron decomposition based on polarization scattering characteristics in sea clutter background is ***,the Cameron decomposition is exploited to fuse the radar echoes of full polarization channels at the data *** to the artificial material structure on the surface of the target,it can be shown that the non-reciprocity of the target cell is stronger than that of the clutter ***,based on the analysis of the decomposition results,a new feature with scattering geometry characteristics in polarization domain,denoted as Cameron polarization decomposition scattering weight(CPD-SW),is extracted as the test statistic,which can achieve more detailed descriptions of the clutter scattering characteristics utilizing the difference between their scattering ***,the superiority of the proposed CPD-SW detector over traditional detectors in improving detection performance is verified by the IPIX measured dataset,which has strong stability under short-time observation in threshold detection and can also improve the separability of feature space zin anomaly detection.

关键词： sea clutter small target radar detection Cameron decomposition characteristics analysis

来源：评论

学校读者我要写书评

暂无评论

A Fuzzy Multi-Objective Framework for Energy Optimization and Reliable Routing in Wireless Sensor Networks via Particle Swarm Optimization

引用

computers, Materials & Continua 2025年第5期83卷 2773-2792页

作者： Medhat A.Tawfeek Ibrahim Alrashdi Madallah Alruwaili Fatma M.Talaat Department of Computer Science College of Computer and Information SciencesJouf UniversitySakaka72341AljoufSaudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72341AljoufSaudi Arabia Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33516Egypt Faculty of Computer Science&Engineering New Mansoura UniversityGamasa35712Egypt

Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past *** work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,*** research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest *** optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting *** address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective *** proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two *** search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing *** PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective *** fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing *** adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network *** proposed multi-objective PSO-fuzzy model is evaluated using NS-3 *** results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art *** proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended net

关键词： Wireless sensor networks particle swarm optimization fuzzy multi-objective framework routing stability

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：