检索结果-内蒙古大学图书馆

32nd IFIP/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2024

作者： Elia, Rafaella Theocharides, Theocharis Kios Research and Innovation Center of Excellence University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus

ISBN: (纸本)9798331539672

Unmanned Ground Vehicles (UGVs) are increasingly used in safety-critical applications, typically controlled under challenging conditions that may cause stress and fatigue on the operator. This can potentially compromise the safety of the mission due to involuntary movements by the operator, resulting in abnormal commands issued on the remote controller of the vehicle. Such movements can be detected by evaluating the mental state of the operator, the operational context of the UGV, and of course real-time movement detection by the operator. To detect such anomalous commands, we propose a three-stage Machine Learning (ML) based approach, which is suitable for embedded implementation providing real-time classification. Firstly, we detect whether there is any movement on the controller and classify the type of the given movement. Next, we classify whether the operator is under incremental stress and finally discern, in relationship to the UGV's operational context extracted by the state of the UGV is considered normal or not. We use a dataset collected through real-world scenarios, to evaluate the proposed approach, and we evaluate the performance of the proposed approach on an embedded platform (Jetson Xavier NX), extracting relevant metrics such as processing time, energy consumption, and classification accuracy. Our findings demonstrate successful high classification rates for the mental state of the operator (96%) and the ground vehicle movements (74%), as well as the associated involuntary command recognition, with low energy (0.43mJ) and time (0.39s) requirements. © 2024 IEEE.

关键词： Remotely operated vehicles

来源：评论

学校读者我要写书评

暂无评论

Inpainting Technique for Removing Vehicle Logos Using Haar-Like and Fast Marching Methods 8

Inpainting Technique for Removing Vehicle Logos Using Haar-L...

引用

8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024

作者： Durmus, Meryem Ergen, Burhan Durmus, Omer Atasoy, Ferhat Samsun University Center for Distance Education Samsun Turkey Firat University College of Engineering Department of Computer Engineering Elazig Turkey Samsun University College of Engineering Department of Software Engineering Samsun Turkey Karabuk University College of Engineering Department of Computer Engineering Karabuk Turkey

ISBN: (纸本)9798331531492

Inpainting is the process of removing an unwanted object or region in an image without degrading the image quality. Inpainting offers a solution to problems such as repairing damaged images or removing unwanted parts of the image. In this study, we focus on the detection of brand logos in vehicle images and the removal of these regions using inpainting. The study consists of two main phases: First, the Haar-like features method is used to detect vehicle logos. Then, the detected logos are removed from the image by applying inpainting with the Fast Marching Method. As a result of the experimental studies, it was found that the methods successfully detected and removed the logos with an accuracy of 98%, and the PSNR value ranged between 25.36 dB and 25.41 dB, and the SSIM value ranged between 0.96692 and 0.96994 while maintaining the image quality. These results show that the proposed method exhibits high performance in removing vehicle logos efficiently. © 2024 IEEE.

关键词： fast marching method haar-like inpainting logo recognition

来源：评论

学校读者我要写书评

暂无评论

A survey of artificial intelligence models for wireless capsule endoscopy videos for superior automatic diagnosis: problems and solutions

引用

Multimedia Tools and Applications 2025年 1-35页

作者： El-Gammal, Eman M. El-Shafai, Walid Taha, Taha E. El-Fishawy, Adel S. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Center of Advanced Software and Biomedical Clinical Engineering Consultations Faculty of Engineering Cairo University Giza Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia

Wireless Capsule Endoscopy (WCE) emerged as an innovative and patient-centric approach for non-invasive and painless examination of the gastrointestinal (GI) tract. It serves as a pivotal tool in helping medical practitioners in the early detection of anomalies within the intricate domain of the human GI tract. The automated identification of aberrations assumes paramount significance, contributing not only to temporal efficiency but also to timely diagnosis. Within the realm of academic literature, a plethora of Artificial Intelligence (AI) methodologies have been proposed to effectuate the automatic classification, segmentation, and synthesis of anomalies inherent in WCE images. This scholarly endeavor undertakes a comprehensive and meticulous survey, elucidating the spectrum of anomaly classification, summarization, and detection techniques harnessed for computer-Aided Diagnosis (CAD) in the context of WCE images. The survey begins by delineating the methodologies underpinning WCE image classification and video processing. Subsequently, an exhaustive evaluation of techniques for analyzing WCE images is furnished, accompanied by an in-depth exploration of pertinent surveys, in addition to a judicious assessment of their merits and demerits. Furthermore, this study undertakes a rigorous evaluation of prevailing datasets utilized to benchmark the efficacy of various WCE techniques. In summary, this survey serves as a vanguard, delineating promising avenues for future investigations in the realm of WCE image analysis models. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Link-Privacy Preserving Graph Embedding Data Publication with Adversarial Learning

引用

Tsinghua Science and Technology 2022年第2期27卷 244-256页

作者： Kainan Zhang Zhi Tian Zhipeng Cai Daehee Seo the Department of Computer Science Georgia State UniversityAtlantaGA 30303USA the Department of Electrical and Computer Engineering George Mason UniversityFairfaxVA 22030USA the National Center of Excellence in Software Sangmyung UniversitySeoul 03016Republic of Korea

The inefficient utilization of ubiquitous graph data with combinatorial structures necessitates graph embedding methods,aiming at learning a continuous vector space for the graph,which is amenable to be adopted in traditional machine learning algorithms in favor of vector *** embedding methods build an important bridge between social network analysis and data analytics,as social networks naturally generate an unprecedented volume of graph data *** social network data not only brings benefit for public health,disaster response,commercial promotion,and many other applications,but also gives birth to threats that jeopardize each individual’s privacy and ***,most existing works in publishing social graph embedding data only focus on preserving social graph structure with less attention paid to the privacy issues inherited from social *** be specific,attackers can infer the presence of a sensitive relationship between two individuals by training a predictive model with the exposed social network *** this paper,we propose a novel link-privacy preserved graph embedding framework using adversarial learning,which can reduce adversary’s prediction accuracy on sensitive links,while persevering sufficient non-sensitive information,such as graph topology and node attributes in graph *** experiments are conducted to evaluate the proposed framework using ground truth social network datasets.

关键词： graph embedding privacy preservation adversarial learning

来源：评论

学校读者我要写书评

暂无评论

RGB Image-Based Hand Pose Estimation: A Survey on Deep Learning Perspective 20

RGB Image-Based Hand Pose Estimation: A Survey on Deep Learn...

引用

20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Farjadi, Seyed Amirhossein Akbarzadeh-T, M.-R. Ghiasi-Shirazi, Kamaledin Ferdowsi University of Mashhad Center of Excellence on Soft Computing and Intelligent Information Processing Department of Computer Engineering Mashhad Iran Ferdowsi University of Mashhad Department of Computer Engineering Mashhad Iran

ISBN: (纸本)9798350383942

The pervasive integration of modern artificial intelligence into daily life necessitates robust human-computer interaction, underscored by advancements in computer technology. As the primary human tool, hand position, and orientation are vital for applications like virtual reality, with hand pose estimation playing a pivotal role. Despite the challenges inherent in RGB image-based estimation, the coalescence of extensive datasets, neural networks, and heightened computational capabilities has catalyzed the utilization of deep learning in visual tasks, particularly advancing hand pose estimation. This review exclusively centers on methodologies of RGB image-based approaches within the realm of hand pose estimation. The paper explores recent advancements in this category, providing a comprehensive analysis of outcomes and charting future directions. Organized around discussions on challenges, advancements, and future directions, this review aims to contribute to the ongoing discourse in the dynamic RGB image-based hand pose estimation field. By addressing unique challenges specific to this method, the paper offers insights that contribute to developing precise and robust hand pose estimation systems, impacting the broader landscape of computer vision and human-machine interaction. © 2024 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Finding the transcription factor binding locations using novel algorithm segmentation to filtration (S2F)

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第9期15卷 3347-3358页

作者： Theepalakshmi, P. Srinivasulu Reddy, U. Department of Computer Science and Engineering Gandhi Institute of Technology and Management Karnataka Bengaluru India Machine Learning and Data Analytics Lab Center of Excellence in Artificial Intelligence Department of Computer Applications National Institute of Technology Tamilnadu Tiruchirappalli India

The primary aim of identifying the binding motifs in gene regulation is to understand the transcriptional regulation molecular mechanism systematically. In this study, the (, d) motif search issue was considered which entails finding the length motifs which differ by at most d substitutions. However, identifying the high-quality pattern (, d) is challenging. It is intended to address the above problem with motif discovery and handle it using the proposed algorithm S2F (Segmentation to Filtration) based on the qPMS (quorum Planted Motif Search) algorithm model. From the entire DNA sequences, five percent are chosen at random to be used in the motif discovery process. This random sub segment (subseg) portion is split up into base, sub k-mers, and its sizes (motif length ()) are determined by the iterative approach. Corresponding to the sizes of and d (mutations), the k-mers are chosen which participated in filtration techniques and the base k-mer count and frequency are updated. The highest frequency of k-mer is recognized as the motif. The algorithm’s performance was evaluated using the two real datasets Escherichia coli cyclic AMP receptor protein (CRP) and mouse Embryonic Stem Cell (mESC) ChIP-seq (Chromatin Immuno Precipitation) dataset. Results from the experiments show that S2F can identify the motifs and appear faster compared to previous state-of-the-art PMS (Planted Motif Search) and qPMS algorithms. Graphical Abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： DNA sequences

来源：评论

学校读者我要写书评

暂无评论

Accurate threat hunting in industrial internet of things edge devices

引用

Digital Communications and Networks 2023年第5期9卷 1123-1130页

作者： Abbas Yazdinejad Behrouz Zolfaghari Ali Dehghantanha Hadis Karimipour Gautam Srivastava Reza M.Parizi Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of Electrical and Software Engineering University of CalgaryAlbertaCanada Department of Mathematics and Computer Science Brandon UniversityBrandonCanada College of Computing and Software Engineering Kennesaw State UniversityGAUSA Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Department of Computer Science and Mathematics Lebanese American UniversityBeirut1102Lebanon

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and *** kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire ***,they can allow malicious software installed on end nodes to penetrate the *** paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge *** proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the Multi-class AdaBoost and majority *** evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.

关键词： IIoT Threat hunting Edge devices Multi-class anomalies Ensemble methods

来源：评论

学校读者我要写书评

暂无评论

3-Multi ranked encryption with enhanced security in cloud computing

引用

Digital Communications and Networks 2023年第2期9卷 313-326页

作者： YeEun Kim Junggab Son Reza M.Parizi Gautam Srivastava Heekuck Oh Major in Bio Artificial Intelligence Dept.of Computer Science and EngineeringHanyang UniversityAnsanRepublic of Korea Department of Computer Science Kennesaw State UniversityMariettaUSA Department of Software Engineering Kennesaw State UniversityMariettaUSA Department of Mathematics and Computer Science Brandon UniversityBrandonCanada Research Center for Interneural Computing China Medical UniversityTaichungTaiwanChina Dept.of Computer Science and Engineering Hanyang UniversityAnsanRepublic of Korea

Searchable Encryption(SE)enables data owners to search remotely stored ciphertexts selectively.A practical model that is closest to real life should be able to handle search queries with multiple keywords and multiple data owners/users,and even return the top-k most relevant search results when *** refer to a model that satisfies all of the conditions a 3-multi ranked search ***,SE schemes that have been proposed to date use fully trusted trapdoor generation centers,and several methods assume a secure connection between the data users and a trapdoor generation *** is,they assume the trapdoor generation center is the only entity that can learn the information regarding queried keywords,but it will never attempt to use it in any other manner than that requested,which is impractical in real *** this study,to enhance the security,we propose a new 3-multi ranked SE scheme that satisfies all conditions without these security *** proposed scheme uses randomized keywords to protect the interested keywords of users from both outside adversaries and the honest-but-curious trapdoor generation center,thereby preventing attackers from determining whether two different queries include the same ***,we develop a method for managing multiple encrypted keywords from every data owner,each encrypted with a different *** evaluation demonstrates that,despite the trade-off overhead that results from the weaker security assumption,the proposed scheme achieves reasonable performance compared to extant schemes,which implies that our scheme is practical and closest to real life.

关键词： Searchable encryption Multi-keyword search Multiple data owners/users Ranked search Enhanced security

来源：评论

学校读者我要写书评

暂无评论

Passivity Preserving Safety-Critical Control of Switched Systems 63

Passivity Preserving Safety-Critical Control of Switched Sys...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Meng, Qingkai Kasis, Andreas Polycarpou, Marios M. University of Cyprus Kios Research and Innovation Center of Excellence Department of Electrical and Computer Engineering Nicosia1678 Cyprus

ISBN: (纸本)9798350316339

System safety refers to the property of the state trajectories to remain within some predefined set at all times. Integrating safety and stability offers significant advantages, such as resilience to disturbances and enhanced reliability and predictability. This paper combines control barrier functions and passivity methodologies, in the context of switched systems, to simultaneously ensure stability and safety. We derive conditions under which the passivity of switched systems is preserved under control barrier function-based switched safety-critical control. This enables the construction of a suitable design framework for observer-based output feedback controllers and switching laws, that achieve simultaneous stability and safety guarantees, without imposing any assumption on the safety of individual subsystems. Furthermore, we show that the simultaneous passivity and safety of interconnected switched systems under feedback and parallel configurations can be guaranteed by applying the developed conditions on each local switched subsystem. The applicability of the developed theoretical results is validated through a planar moving body example. © 2024 IEEE.

关键词： Feedback control

来源：评论

学校读者我要写书评

暂无评论

A Secure and Efficient Biometric Template Protection Scheme for Palmprint Recognition System

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1051-1063页

作者： Sardar, Alamgir Umer, Saiyed Rout, Ranjeet Kumar Khan, Muhammad Khurram Aliah University Department of Computer Science and Engineering Kolkata700156 India National Institute of Technology Department of Computer Science and Engineering Srinagar190006 India King Saud University Center of Excellence in Information Assurance Riyadh11451 Saudi Arabia

The accuracy and security of a biometric system are the two sides of a coin. A biometric system must be simple, flexible, efficient, and secure enough from unauthorized access. Concerning these requirements, this article presents an enhanced palmprint recognition system with superior performance and improved biometric template protection schemes. This method comprises five components: image preprocessing, feature extraction, cancelable biometrics, classification, and Bio-Cryptosystem. The palm texture region is extracted from the input hand image during preprocessing. A feature representation technique is then used to extract discriminant features from the palmprint texture patterns. The extracted features are then analyzed using an information coding scheme to compute a user-specific token. Here, the user-specific tokens along with the original palmprint features are used to calculate the feature vectors for the cancelable biometric system. A novel Bio-Cryptosystem has been proposed to protect templates with high security where there is no need to remember the users' tokens. Cancelable feature vectors are kept online in encrypted form using the proposed Bio-Cryptosystem, which is used to identify or verify the subjects after decryption. The original feature vectors are kept offline to prevent these from external attacks and misuse. Finally, the multiclass linear support vector machine has been used for user classification. For experimental purposes, two benchmark hand image databases: BOSPHORUS and CASIA-Palmprint, are employed, and the proposed system has achieved nearly 100% correct recognition rate in cancelable domain for both the employed databases. Finally, the performance comparison in terms of both verification and identification for the palmprint and the cancelable palmprint recognition systems with the existing state-of-the-art methods shows the superiority of the proposed system. © 2020 IEEE.

关键词： Palmprint recognition

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：