检索结果-内蒙古大学图书馆

Sea Surface Temperature Prediction Based on Spatio-Temporal Graph Contrastive Learning Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 14228-14239页

作者： Dai, Weihan He, Xiaoyu Geng, Xiulin Zhang, Shuai Gao, Ziheng Zhejiang Sci-Tech University School of Computer Science and Technology Hangzhou310018 China Hangzhou Dianzi University School of Communication Engineering Hangzhou310018 China Shanghai University School of Computer Engineering and Science Shanghai200444 China

There is a growing interest in using spatio-temporal graph networks to predict sea surface temperature (SST). Nevertheless, numerous existing methodologies struggle to accurately capture both local and global spatial dependencies and are red frequently vulnerable to data noise. To tackle these challenges, we introduce a novel framework known as Spatio-Temporal Graph Contrastive Learning Network (STGLN), which enhances the precision of sea surface temperature forecasts. Notably, STGLN employs both feature-level and topology-level data augmentation techniques to alleviate the influence of data noise. Subsequently, the refined SST feature matrix and adjacency matrix are analyzed through a dual-branch network with shared parameters, specifically designed to effectively capture both local and global spatial dependencies within the SST time series data. Furthermore, we propose an auxiliary task for spatio temporal contrastive learning, which aims to mitigate the sparsity of supervised signals and to efficiently extract essential spatio temporal information. Comprehensive experiments conducted on real-world SST datasets demonstrate that STGLN significantly surpasses other advanced methodologies. © 2008-2012 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Sports Events Recognition Using Multi Features and Deep Belief Network

引用

computers, Materials & Continua 2024年第10期81卷 309-326页

作者： Bayan Alabdullah Muhammad Tayyab Yahay AlQahtani Naif Al Mudawi Asaad Algarni Ahmad Jalal Jeongmin Park Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science Applied CollegeKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

In the modern era of a growing population,it is arduous for humans to monitor every aspect of sports,events occurring around us,and scenarios or *** recognition of different types of sports and events has increasingly incorporated the use of machine learning and artificial *** research focuses on detecting and recognizing events in sequential photos characterized by several factors,including the size,location,and position of people’s body parts in those pictures,and the influence around those *** approaches utilized,here are feature descriptors such as MSER(Maximally Stable Extremal Regions),SIFT(Scale-Invariant Feature Transform),and DOF(degree of freedom)between the joint points are applied to the skeleton ***,for the same purposes,other features such as BRISK(Binary Robust Invariant Scalable Keypoints),ORB(Oriented FAST and Rotated BRIEF),and HOG(Histogram of Oriented Gradients)are applied on full body or *** integration of these techniques increases the discriminative nature of characteristics retrieved in the identification process of the event,hence improving the efficiency and reliability of the entire *** extracted features are passed to the early fusion and DBscan for feature fusion and *** deep belief,network is employed for *** results demonstrate a separate experiment’s detection average recognition rate of 87%in the HMDB51 video database and 89%in the YouTube database,showing a better perspective than the current methods in sports and event identification.

关键词： Machine learning silhouettes extremal regions joint points scalable keypoints

来源：评论

学校读者我要写书评

暂无评论

The Internet of Trust: Securing and Transparent Supply Chains with Blockchain and IoT 18

The Internet of Trust: Securing and Transparent Supply Chain...

引用

18th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Singal, Gaurav Kushwaha, Riti Sharma, Ashish Tewari, Tulika Netaji Subhash University of Technology SMIEEE Computer Science and Engineering Delhi India Bennett University School of Computer Science and Technology Greater Noida India Manipal University Computer Science and Engineering Jaipur India Netaji Subhash University of Technology Computer Science and Engineering Delhi India

ISBN: (纸本)9798350391725

In an era where digital commerce continues to burgeon, the conventional supply chain confronts challenges of inefficiency, fraud, and a dearth of transparency. Blockchain, renowned for its decentralized and immutable ledger, emerges as a compelling solution to transform the e-commerce supply chain landscape. In conventional supply chain practices marked by centralized databases and manual record-keeping, inefficiencies and a dearth of transparency are widespread. Challenges stemming from cumbersome paperwork, delayed information flow, and vulnerability to errors hindered effective coordination, traceability, and overall operational efficiency. Blockchain and IoT can elevate e-commerce supply chains by ensuring transparent, secure, and automated data-sharing, fostering efficiency and trust throughout the entire process. We have presented an Ethereum-based blockchain and Internet of Things e-commerce platform in this paper. We describe in detail how to put in place a system that stores a product's journey's details on an immutable distributed ledger. This allows for secure tracing of a product's origin. The prototype of the system is deployed and tested on Hardhat testing framework. Traditional databases and cloud storages have been replaced by blockchain and IPFS. IPFS is used as the decentralized and distributed storage layer, facilitating the secure and efficient storage of credentials. Furthermore, the results of our experiments and security and scalability analyses demonstrate the viability of our suggested model. © 2024 IEEE.

关键词： Distributed ledger

来源：评论

学校读者我要写书评

暂无评论

Webcam-Based OCR System with Text-to-Speech Conversion 5

Webcam-Based OCR System with Text-to-Speech Conversion

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Nair, Rekha R Babu, Tina Kishore, S. Poornima, J. Sambasivudu, Madduru Bhargavi, Manchikalapudi Alliance School of Advanced Computing Alliance University Department of Computer Science and Engineering Bengaluru India Department of Computer Applications Mangalore India Brindavan College of Engineering Department of Information Science and Engineering Bengaluru India Malla Reddy College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331530013

The project develops an OCR system that converts webcam-captured text to speech, featuring user registration for personalized experiences. Key components include image capture via webcam, text extraction using OCR, database storage, and text-to-speech conversion. The system employs Python, OpenCV for image processing, Tesseract for OCR, and Google Text-to-Speech for audio output. Main objectives are to streamline text digitization and assist visually impaired users. The modular design allows for future enhancements like language translation. Comprehensive testing ensures reliability and effectiveness. The system demonstrates an efficient solution for converting printed text to digital and audio formats, with applications in document digitization, education, and accessibility services. It reduces manual effort in text digitization and improves access to written information for visually impaired individuals, showcasing potential across various fields. © 2024 IEEE.

关键词： Optical character recognition

来源：评论

学校读者我要写书评

暂无评论

Risk-Aware Multi-Agent Multi-Armed Bandits 24

Risk-Aware Multi-Agent Multi-Armed Bandits

引用

2024 International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, MobiHoc 2024

作者： Shao, Qi Ye, Jiancheng Lui, John C.S. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong School of Computer Science and Engineering Macau University of Science and Technology China

ISBN: (纸本)9798400705212

Multi-armed bandits (MAB) is an online learning and decision-making model under uncertainty. Instead of maximizing the expected utility (or reward) in a classical MAB setting, the variance of the utility should be considered when making risk-aware decisions. In this paper, we propose a risk-aware multi-agent MAB (MAMAB) model, which considers both the "independent" and "correlated" risk when multiple agents make arm-pulling decisions. Specifically, the system includes a platform that owns a number of tasks (or arms) awaiting a group of agents to accomplish. We show how to calculate the arm-pulling strategy of agents with potentially different eligible arm sets under a Nash equilibrium point. From the perspective of the platform, each arm has its maximal capacity to accommodate arm-pulling agents. We design the platform’s optimal payment algorithms for its risk-aware revenue maximization (a regret minimization) under both independent and correlated risks. We prove that our algorithms achieve the sub-linear regret under independent risks when the platform can or cannot differentiate the utility on each arm. We also prove that our algorithm achieves the sub-linear regret under correlated risks. We also carry out experiments to quantify the merits of our algorithms for various networking applications, such as crowdsourcing and edge computing. © 2024 Copyright held by the owner/author(s).

关键词： Crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal crowds features extraction of infrared images using neural network

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2543-2556页

作者： Al-Oraiqat, Anas M. Drieiev, Oleksandr Drieieva, Hanna Meleshko, Yelyzaveta AlRawashdeh, Hazim Al-Oraiqat, Karim A. Hasan, Yassin M. Y. Maricar, Noor Khan, Sheroz Department of Computer Science College of Engineering and Information Technology Onaizah Colleges Qassim Saudi Arabia Department of Cybersecurity and Software Central Ukrainian National Technical University Kropyvnytskyi Ukraine Department of Artificial Intelligence Faculty of Information Technology Zarqa University Zarqa Jordan Department of Electrical Engineering College of Engineering and Information Technology Onaizah Colleges Qassim Saudi Arabia

Crowds can lead up to severe disasterous consequences resulting in fatalities. Videos obtained through public cameras or captured by drones flying overhead can be processed with artificial intelligence-based crowd analysis systems. Being a hot area of research over the past few years, the goal is not only to identify the presence of crowds but also to predict the probability of crowd-formation in order to issue timely warnings and preventive measures. Such systems will significantly reduce the probablity of the potential disasters. Developing effective systems is a challenging task, especially due to factors such as naturally occuring diverse conditions, variations in people or background pixel areas, noise, behaviors of individuals, relative amounts/distributions/directions of crowd movements, and crowd building reasons. This paper proposes an infrared video processing system based on U-Net convolutional neural network for crowd monitoring in infrared video frames to help estimate the people crowd with normal or abnormal trends. The proposed U-Net architecture aims to efficiently extract crowd features, achieve sufficient people marking-up accuracy, competitively with optimal network configurations in terms of the depth and number of filters to consequently minimise the number of coefficients. For further faster processing, hardware resources/implementation area savings, and lower power, the optimized network coefficients measured are represented in Canonic-Signed Digit with minimal number of nonzero (± 1) digits, minimizing the number of underlying shift-add/subtract operations of all multipliers. The achieved significantly reduced computational cost makes the proposed U-Net effectively suitable for resource-constrained and low power applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

引用

CAAI Transactions on Intelligence technology 2024年第4期9卷 1031-1041页

作者： Meng Liu Jianwei Niu Yu Liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

来源：评论

学校读者我要写书评

暂无评论

Enhanced Object Detection and Classification via Multi-Method Fusion

引用

computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： Muhammad Waqas Ahmed Nouf Abdullah Almujally Abdulwahab Alazeb Asaad Algarni Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classification and object detection *** proposed approach involves the integration ofmultiple methods in a complementary *** process commences with the application of Gaussian filters tomitigate the impact of noise *** images are then processed for segmentation using Fuzzy C-Meanssegmentation in parallel with saliency mapping techniques to find the most prominent *** Binary RobustIndependent Elementary Features(BRIEF)characteristics are then extracted fromdata derived fromsaliency mapsand segmented *** precise object separation,Oriented FAST and Rotated BRIEF(ORB)algorithms *** Algorithms(GAs)are used to optimize Random Forest classifier parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A significant enhancement hasbeen achieved by integrating Genetic Algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of our system but also amplifies its overall *** proposed methodologyhas demonstrated notable classification accuracies of 90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of 87.2%and 86.6%have been *** ourmethod performed well in both datasets it may face difficulties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration for parameter optimization shows a notablestrength in enhancing the overall adaptability and performance of our system.

关键词： BRIEF features saliency map fuzzy c-means object detection object recognition

来源：评论

学校读者我要写书评

暂无评论

Frequency Agile Strategy Design of Radar Network for Wideband Sweep Jamming via Coalition Formation Game

引用

IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 7906-7919页

作者： Liao, Maosen Xiong, Kui Zhang, Long Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China School of Information and Communication Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Chengdu611731 China

This article proposes an intelligent frequency agile design strategy for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several non-overlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multi-agent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile design strategy, a joint coalition formation game and distributed Q-learning algorithm (CFDQ) is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies. © 1965-2011 IEEE.

关键词： Jamming

来源：评论

学校读者我要写书评

暂无评论

Alfred: Open-Source Autonomous Mobile Robot Platform with Augmented Physical Testbed 8

Alfred: Open-Source Autonomous Mobile Robot Platform with Au...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Naresh, Vishwesh Vhavle Kumar Sharma, Jatin Indraprastha Institute of Information Technology Delhi Department of Computer Science Engineering New Delhi India

ISBN: (纸本)9798350376425

This research study introduces Alfred, a novel open-source Autonomous Mobile Robot (AMR) platform and a physical testbed that enables the integration of virtual scenarios. This system allows for the development and evaluation of algorithms for localization, perception, and path planning in a safe and efficient manner. By combining virtual and physical elements, our camera-based localization testbed facilitates comprehensive testing of AMRs, ensuring their readiness for real-world deployment. The modular design of Alfred, with parts sourced within the Indian subcontinent, makes it a cost-effective and adaptable solution for robotics research and development. We demonstrate the effectiveness of our platform through experiments in localization, mapping, and navigation, showcasing its potential for advancing AMR technology. © 2024 IEEE.

关键词： Machine design

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：