检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Zeng, Hongye Zou, Ke Chen, Zhihao Gao, Yuchong Chen, Hongbo Zhang, Haibin Zhou, Kang Wang, Meng Goh, Rick Siow Mong Liu, Yong Jiang, Chang Zheng, Rui Fu, Huazhu School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China University of Chinese Academy of Sciences Beijing China National Key Laboratory of Fundamental Science on Synthetic Vision College of Computer Science Sichuan University Chengdu China College of Intelligence and Computing Tianjin University Tianjin China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Beth Israel Deaconess Medical Center Harvard Medical School Boston United States Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore Department of Orthopedics Zhongshan Hospital Fudan University Shanghai China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai China

Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data. In this study, we propose the Training-free Image Style Alignment (TISA) framework to align the style of handheld device data to those of standard devices. The proposed TISA can directly infer handheld device images without extra training and is suited for clinical applications. We show that TISA performs better and more stably in medical detection and segmentation tasks for handheld device data. We further validate TISA as the clinical model for automatic measurements of spinal curvature and carotid intima-media thickness. The automatic measurements agree well with manual measurements made by human experts and the measurement errors remain within clinically acceptable ranges. We demonstrate the potential for TISA to facilitate automatic diagnosis on handheld ultrasound devices and expedite their eventual widespread use. © 2024, CC BY-NC-SA.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

引用

Financial Innovation 2023年第1期9卷 2939-2991页

作者： Zhen‑Song Chen Jia Zhou Chen‑Ye Zhu Zhu‑Jun Wang Sheng‑Hua Xiong Rosa M.Rodríguez Luis Martínez Mirosław J.Skibniewski School of Civil Engineering Wuhan UniversityWuhan 430072China College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan 618307China School of Management Xi’an Jiaotong UniversityXi’an 710049China Department of Computer Science University of Jaén23071 JaénSpain Department of Civil and Environmental Engineering University of MarylandCollege ParkMD 20742‑3021USA Institute for Theoretical and Applied Informatics Polish Academy of SciencesGliwicePoland Chaoyang University of Technology TaizhongTaiwan

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and *** the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment ***,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate ***,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment *** improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making ***,a credit risk assessment index for Chinese real estate enterprises is ***,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II *** approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation ***,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and *** study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

关键词： Real estate enterprise Credit risk assessment PROMETHEE II Best–worst method Proportional hesitant fuzzy linguistic term sets

来源：评论

学校读者我要写书评

暂无评论

ReconBoost: Boosting Can Achieve Modality Reconcilement

arXiv

引用

arXiv 2024年

作者： Hua, Cong Xu, Qianqian Bao, Shilong Yang, Zhiyong Huang, Qingming Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores a novel multi-modal alternating learning paradigm pursuing a reconciliation between the exploitation of uni-modal features and the exploration of cross-modal interactions. This is motivated by the fact that current paradigms of multi-modal learning tend to explore multi-modal features simultaneously. The resulting gradient prohibits further exploitation of the features in the weak modality, leading to modality competition, where the dominant modality overpowers the learning process. To address this issue, we study the modality-alternating learning paradigm to achieve reconcilement. Specifically, we propose a new method called ReconBoost to update a fixed modality each time. Herein, the learning objective is dynamically adjusted with a reconcilement regularization against competition with the historical models. By choosing a KL-based reconcilement, we show that the proposed method resembles Friedman's Gradient-Boosting (GB) algorithm, where the updated learner can correct errors made by others and help enhance the overall performance. The major difference with the classic GB is that we only preserve the newest model for each modality to avoid overfitting caused by ensembling strong learners. Furthermore, we propose a memory consolidation scheme and a global rectification scheme to make this strategy more effective. Experiments over six multi-modal benchmarks speak to the efficacy of the method. We release the code at https://***/huacong/ReconBoost. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Multiple Postures and Behaviors Recognition Method for Horse Based Onimproved Slowfast Network

SSRN

引用

SSRN 2024年

作者： Liu, YanHong Li, JinXing Zhou, Fang Chen, XinWen Bai, Tao Wei, Zhangliang Zheng, WenXin Guo, LeiFeng College of Computer and Information Engineering Xinjiang Agricultural University Urumqi830052 China Agricultural Information Institute Chinese Academy of Agricultural Sciences Beijing100080 China Institute of Animal Husbandry Quality Standards Xinjiang Academy of Animal Science Urumqi830011 China College of Information Science and Technology Shihezi University Shihezi832000 China Intelligent Agriculture Engineering Research Center of the Ministry of Education Urumqi830011 China Xinjiang Agricultural Informatization Engineering Technology Research Center Urumqi830011 China

The sleeping and grazing behaviors of horses play a crucial role in their health and welfare. In the horse industry,with the prevalent trend of individual single-stall farming in stable, accurately identifying various behaviors of horses within stables is imperative. This study has established a spatio-temporal dataset for horse postures and behaviors,proposed an algorithm utilizing a SlowFast network with an enhanced loss function. This algorithm achieves automatic recognition of multiple postures and behaviors of horse simultaneously. The model developed in this study demonstrates high accuracy in identifying three postures within the stable: Standing, Crouching, and Lying, achieving respective accuracies of 91.43%, 91.81%, and 91.74%. Additionally, it accurately recognizes two behaviors: Sleeping and Grazing, achieving best accuracies of 89.06% and 97.75%. The overall best accuracy of the model is 92.36%. Experiments on video recognition confirm that the suggested model recognizes horse video data *** study marks the first time computer vision technology has been used in the horse farming industry,achieving non-intrusive recognition of multiple horse postures and *** study provides valuable data support for livestock managers to evaluate the health conditions of horses, enhances the welfare of horses in stables,and contributes to the advancement of modern horse husbandry practices. © 2024, The Authors. All rights reserved.

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

Customize your NeRF: Adaptive Source Driven 3D Scene Editing via Local-Global Iterative Training

Customize your NeRF: Adaptive Source Driven 3D Scene Editing...

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Runze He Shaofei Huang Xuecheng Nie Tianrui Hui Luoqi Liu Jiao Dai Jizhong Han Guanbin Li Si Liu Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences MT Lab Meitu Inc. School of Computer Science and Information Engineering Hefei University of Technology Sun Yat-sen University Institute of Artificial Intelligence Beihans University Hangzhou Innovation Institute Beihang University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

In this paper, we target the adaptive source driven 3D scene editing task by proposing a CustomNeRF model that unifies a text description or a reference image as the editing prompt. However, obtaining desired editing results conformed with the editing prompt is nontrivial since there exist two significant challenges, including accurate editing of only foreground regions and multi-view consistency given a single-view reference image. To tackle the first challenge, we propose a Local-Global Iterative Editing (LGIE) training scheme that alternates between foreground region editing and full-image editing, aimed at foreground-only manipulation while preserving the background. For the second challenge, we also design a class-guided regularization that exploits class priors within the generation model to alleviate the inconsistency problem among different views in image-driven editing. Extensive experiments show that our CustomNeRF produces precise editing results under various real scenes for both text- and image-driven settings. The code is available at: https://***/hrz2000/CustomNeRF.

关键词： Training Adaptation models Solid modeling computer vision Three-dimensional displays Codes Accuracy

来源：评论

学校读者我要写书评

暂无评论

Solving Boolean polynomial systems by parallelizing characteristic set method for cyber-physical systems

Solving Boolean polynomial systems by parallelizing characte...

引用

作者： Zhao, Juan Zhu, Min Li, Xiaoyong Huang, Zhenyu Li, Jincai Song, Junqiang College of Meteorology and Oceanography National University of Defense Technology Changsha China College of Computer Science and Technology National University of Defense Technology Changsha China SKLOIS Institute of Information Engineering Chinese Academy of Sciences Beijing China

Many cyber-attach schemes and coding models established by algebra tools are build to address the problem of security of cyber-pysical systems (CPS). As an important field of algebra computing, Boolean Polynomial System Solving (PoSSo) problem plays a very important role in many algebra applications. In this article, we propose an efficient Parallel Boolean Characteristic Set method (PBCS) under the high-performance computing environment to improve the efficiency of solving Boolean polynomial systems. The PBCS is implemented based on the state-of-the-art Boolean Characteristic Set method (BCS). It adopts a master-slave parallel pattern, and distributes tasks based on the polynomial sets after initial zero decomposition. We design a strategy of dynamically reallocating tasks to ameliorate load imbalance, which is caused by dynamical zero decomposition of polynomials. Furthermore, we improve its performance by optimizing the parameter settings of PBCS, including the maximum number of polynomial branches that trigger the dynamic allocation policy and the scheduling time. Experimental results with solving several Boolean polynomial systems confirm that PBCS is efficient and scalable, especially for the equations generating from stream ciphers that have block triangular structure. Moreover, the method also has good scalability. It shows a stable speedup as well even extending to the size of thousands of CPU cores. © 2020 John Wiley & Sons Ltd.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Power Quality Enhancement of Solar Based Microgrids Using ML and AI

Power Quality Enhancement of Solar Based Microgrids Using ML...

引用

Technological Advancements in Computational sciences (ICTACS), International Conference on

作者： K. Paul Joshua C. Vennila Kurikyala Prasad Yadav D. Kirubakaran Vartika Kulshrestha B.R. Praveen Department of Electronics and Communication Engineering St. Peter's College of Engineering and Technology Tamil Nadu India Department of Electrical and Electronics Engineering Alagappa Chettiar Government College of Engineering and Technology Tamil Nadu India Engineering Department University of Technology and Applied Sciences-Ibri (UTAS-Ibri) Dept. of Electrical and Electronics Eng. St. Joseph's Institute of Technology Tamil Nadu India Computer Science & Engineering ACED Alliance University-Central Campus Karnataka India Dept. of Electrical and Electronics Engineering Sai Vidya Institute of Technology Karnataka India

ISBN: (数字)9798350387490

ISBN: (纸本)9798350387506

Solar-powered micro grids are gaining popularity as a cost-effective and environmentally friendly way to provide localized electricity. Microgrids struggle with solar power's fluctuation and intermittent nature. Sun-based microgrids' power quality is improved via machine learning (ML) and synthetic intelligence (AI). The recommended solution employs modern ML algorithms to predict solar power generation and micro grid energy output variations. ML models can accurately forecast changes in solar irradiance, temperature, and other crucial aspects by evaluating ancient and real-time data, enabling proactive micro grid power float management. The proposed ML and AI-based technology offers superior power best, proactive power control, and better predictions than standard management methods. Simulation and experimental results show that the technique reduces load interruptions, improves balance, and reduces solar energy oscillations on the micro grid. Its capabilities are excellent. to provide reliable and excellent power supply, large-scale renewable energy adoption, and sustainable power ecosystems with ML and AI in solar-based micrgarids.

关键词： Solar irradiance Renewable energy sources Temperature distribution Statistical analysis Power quality Microgrids Real-time systems Solar power generation Standards Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

Expression of Concern for: An Advanced Analysis of Disease Prediction and Prevention Using Machine Learning

Expression of Concern for: An Advanced Analysis of Disease P...

引用

Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), IEEE International Conference on

作者： Karuppasamy M M.Jansi Rani Mahesh Kotha Suma S T. Subburaj Haji Begum K. Suthendran Department of Computer Applications Kalasalingam Academy of Research and Education Krishnankoil India Department of Computer Science and Engineering Mepco Schlenk Engineering College Sivakasi Virudhunagar India Department of CSE (AI&ML) CMR Technical Campus Hyderabad Telangana India Department of CSE CMR Technical Campus Hyderabad Telangana India Department of Computer Science and Engineering RajaRajeshwari College of Engineering Bangalore India Department of ECE Shadan Women's college of Engineering and Technology Hyderabad Telangana India Department of Information Technology Kalasalingam Academy of Research and Education Krishnankoil India

ISBN: (数字)9798350338287

ISBN: (纸本)9798350338294

On demand of overgrowing population crop production should be increased to satisfy the daily needs. Nowadays, diseases in crops are increasing. The various disease lead to decrease in the yield of crop production. In the proposed work machine learning techniques are used to identify the disease in crops and take precautionary measures to avoid the disease spread in crops. Based on the investigation, the parameters like rainfall, soil type, temperature leads to the spreading of diseases in crops. Kclosest Neighbor concept is used for analysis of various soil groups. For enhancement of the work support vector machine for crop characterization, straight relapse and ID3algorithm is used for disease prediction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Using InterCloudFramework to migrate application and data between two public clouds 7

Using InterCloudFramework to migrate application and data be...

引用

7th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2021

作者： Koushik, S Patil, Annapurna P. Suma, C.S. M. S. Ramaiah Institute of Technology Dept. of Computer Science and Engineering Bengaluru India Dayananda Sagar Academy of Technology and Management Department of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9781665428491

Cloud computing is an emerging computing platform for sharing resources over the internet, including infrastructure, applications, software, and business processes. Cloud computing is popular because of its public presentation, least cost, high availability. These days, many organizations use cloud services for their business activities to enhance their computing resource capabilities at lower prices. Cloud computing plays a vital role in research and academia to share resources and improve the teaching-learning process. One of the Cloud platforms' drawbacks is the data and application tightly coupled with the Cloud Service called Vendor Lock-In. Methods and procedures are available to migrate live data within the same cloud service providers. But to migrate the applications or data from one cloud service provider to another cloud service provider is complex. The paper proposes a novel methodology for migrating the application or data from one cloud service provider to another cloud service provider. The proposed approach presents CPU and RAM usage for the migration of applications or data. The paper also provides insights into the time taken for the Live Migration between heterogeneous clouds. © 2021 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Detailed Review on Challenges in the Computational Frameworks in Building 6G for Healthcare System

A Detailed Review on Challenges in the Computational Framewo...

引用

Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： M Shalini Rupesh Sharma M. Bhuvaneswari Arti Badhoutiya M Madan Mohan S P V Subba Rao Department of Electronics and Communication Engineering (ECE) Prince Shri Venkateshwara Padmavathy Engineering College TN Department of Electronics & Communication Engineering (ECE) IES Institute of Technology and Management IES University Bhopal M.P India Department of Biomedical Engineering (BME) Karpagam Academy of Higher Education Coimbatore Department of Electrical Engineering (EE) GLA University Mathura Department of Computer science and Engineering (C S & E) Nehru Institute of Engineering and Technology T.M.Palayam Tamil Nadu India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and Technology Hyderabad

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

In the modern age of Sixth-generation (6G) connections, the merging of the Intellect Internet of Issues (IIoT) plays a crucial part in improving storage and processing of data powers. The core goal of 6 G is to provide extremely small delay, high speed, and improved quality of service so as to enable smooth contact among network points. Within the medical industry, it is important to fit all facilities at state-ofthe-art technology to allow clever diagnoses, patient-centric therapies, and a range of healthcare services, outside the confines of a medical facility and online. To ensure the health care sector’s readiness and flexibility to cutting-edge technology, giving varied uses from robotic treatments to remote patient tracking via portable technologies in Active Adaptive Living (AAL) environments is important. The intelligent connecting platform serves as the backbone, managing various networking hubs and input devices to offer time-sensitive healthcare services. This paper presents a new reference layered communication system designed for realtime conversation among nodes and devices. By studying the future aspects of the 6 G system, the paper shows its potential uses in healthcare, hoping to improve treatment effectiveness and smartly combine services. The suggested structure attempts to build a strong basis for the changing world of healthcare apps in the framework of 6 G technology.

关键词： 6G mobile communication Industries Technological innovation Wireless networks Merging Virtual environments Medical services

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：