检索结果-内蒙古大学图书馆

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Huang, Xiaofei Chen, Wenting Liu, Jie Lu, Qisheng Luo, Xiaoling Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

ISBN: (纸本)157735897X

Medical report generation is crucial for clinical diagnosis and patient management, summarizing diagnoses and recommendations based on medical imaging. However, existing work often overlook the clinical pipeline involved in report writing, where physicians typically conduct an initial quick review followed by a detailed examination. Moreover, current alignment methods may lead to misaligned relationships. To address these issues, we propose DAMPER, a dual-stage framework for medical report generation that mimics the clinical pipeline of report writing in two stages. In the first stage, a MeSH-Guided Coarse-Grained Alignment (MCG) stage that aligns chest X-ray (CXR) image features with medical subject headings (MeSH) features to generate a rough keyphrase representation of the overall impression. In the second stage, a Hypergraph-Enhanced Fine-Grained Alignment (HFG) stage that constructs hypergraphs for image patches and report annotations, modeling high-order relationships within each modality and performing hypergraph matching to capture semantic correlations between image regions and textual phrases. Finally,the coarse-grained visual features, generated MeSH representations, and visual hypergraph features are fed into a report decoder to produce the final medical report. Extensive experiments on public datasets demonstrate the effectiveness of DAMPER in generating comprehensive and accurate medical reports, outperforming state-of-the-art methods across various evaluation metrics. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge Regression

Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge...

引用

Artificial Intelligence, Applications, Innovation and Ethics (AI2E), International Conference for

作者： Manel Marweni Majdi Mansouri Mansour Hajji Mohamed Faouzi Mimouni Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Muscat Oman Laboratory of Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine Tunisia

ISBN: (数字)9798331513733

ISBN: (纸本)9798331513740

The modern energy landscape is undergoing a seismic change from traditional, finite energy sources and toward cleaner, renewable alternatives. The restrictions faced by traditional sources, which are not only finite but increasingly shrink in the face of burgeoning global energy demands driven by population increase and industrial expansion, are driving this change. Although promising, renewable energy poses complications, particularly the reliance on climatic conditions. An important aspect of addressing these difficulties is effective energy management within distribution systems, which includes forecasting and optimization phases. This research focuses on forecasting using an advanced machine learning (ML) approach. Accurately forecasting renewable energy generation over time is critical for improving energy management. This technique is evaluated using a variety of performance indicators, including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R 2 ). Empirical studies support the method's usefulness, demonstrating noteworthy performance with low error rates.

关键词： Photovoltaic systems Renewable energy sources Technological innovation Accuracy Machine learning Predictive models Forecasting Kernel Energy management Optimization

来源：评论

学校读者我要写书评

暂无评论

Constrained Energy Minimization (CEM) for Hyperspectral Target Detection: Theory and Generalizations

引用

IEEE Transactions on Geoscience and Remote Sensing 2024年 62卷

作者： Chang, Chein-I. Information and Technology College Dalian116026 China University of Maryland Baltimore County Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering BaltimoreMD21250 United States National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan

Target detection is a fundamental task of hyperspectral imaging where constrained energy minimization (CEM) has been widely used for subpixel target detection techniques. Due to its effectiveness, CEM has been generalized to various versions, such as kernel CEM (KCEM), kernel target-constrained interference-minimized filter (KTCIMF), ensemble cascaded CEM (ECEM), and hierarchical CEM (HCEM). Unfortunately, these generalizations overlooked the key design rationale behind CEM. This article revisits CEM for hyperspectral target detection (HTD) and proves how and why it works mathematically. Specifically, several new CEM generalizations are derived and particularly noteworthy. By including spatial information in an iterative process, KCEM, ECEM, and HCEM can be generalized to iterative KCEM (IKCEM), iterative KTCIMF (IKTCIMF), iterative ECEM (IECEM), and iterative HCEM (IHCEM). Also, by utilizing an iterative random training sampling (IRTS) to generate the desired target signature to be detected, these algorithms are further generalized to IRTS KCEM (IRTS-KCEM), IRTS ECEM (IRTS-ECEM), and IRTS HCEM (IRTS-HCEM). A comprehensive analysis along with comparative study on these generalizations is conducted through extensive experiments to demonstrate the effectiveness of IKCEM, IHCEM, and IECEM. © 1980-2012 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Exploration of Data Scene Characterization and 3D ROC Evaluation for Hyperspectral Anomaly Detection

引用

Remote Sensing 2024年第1期16卷

作者： Chang, Chein-I Chen, Shuhan Zhong, Shengwei Shi, Yidan Information and Technology College Dalian Maritime University Dalian116026 China Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland BaltimoreMD21250 United States Department of Electrical Engineering National Cheng Kung University Tainan70101 Taiwan Department of Electrical Engineering Zhejiang University Hangzhou310027 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

Whether or not a hyperspectral anomaly detector is effective is determined by two crucial issues, anomaly detectability and background suppressibility (BS), both of which are very closely related to two factors, the datasets used for a selected hyperspectral anomaly detector and detection measures used for its performance evaluation. This paper explores how anomaly detectability and BS play key roles in hyperspectral anomaly detection (HAD). To address these two issues, we investigate three key elements attributed to HAD. One is a selected hyperspectral anomaly detector, and another is the datasets used for experiments. The third one is the detection measures used to evaluate the effectiveness of a hyperspectral anomaly detector. As for hyperspectral anomaly detectors, twelve commonly used anomaly detectors were evaluated and compared. To address the appropriate use of datasets for HAD, seven popular and widely used datasets were studied for HAD. As for the third issue, the traditional area under a receiver operating characteristic (ROC) curve of detection probability—PD versus false alarm probability, PF, (AUC(D,F))—was extended to 3D ROC analysis where a 3D ROC curve was developed to generate three 2D ROC curves from which eight detection measures could be derived to evaluate HAD in all round aspects, including anomaly detectability, BS and joint anomaly detectability and BS. Qualitative analysis showed that many works reported in the literature which claimed that their developed hyperspectral anomaly detectors performed better than other anomaly detectors are actually not true because they overlooked these two issues. Specifically, a comprehensive study via extensive experiments demonstrated that these 3D ROC curve-derived detection measures can be further used to address the various characterizations of different data scenes and also to provide explanations as to why certain data scenes are not suitable for HAD. © 2023 by the authors.

关键词： Curve fitting

来源：评论

学校读者我要写书评

暂无评论

DAMPER: A Dual-Stage Medical Report Generation Framework with Coarse-Grained MeSH Alignment and Fine-Grained Hypergraph Matching

arXiv

引用

arXiv 2024年

关键词： Coarse-grained modeling

来源：评论

学校读者我要写书评

暂无评论

A Survey on Network Management for xANET: Evolution, Challenges, Future Directions

引用

IEEE Communications Surveys and Tutorials 2025年

作者： Li, Tong Yang, Chungang Wang, Yao Cai, Lin Anpalagan, Alagan Han, Zhu Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China National Key Laboratory of Multi-domain Data Collaborative Processing and Control Xi'an710068 China Hangzhou Institute of Technology of Xidian University Hangzhou311231 China University of Victoria Department of Electrical and Computer Engineering VictoriaBCV8P 5C2 Canada Ryerson University Department of Electrical and Computer Engineering TorontoONM5B 2K3 Canada University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446701 Korea Republic of

The x ad hoc network (xANET) termed as a family of ad hoc networks, including mobile ad hoc network (MANET), vehicular ad hoc network (VANET), flying ad hoc network (FANET) and satellite ad hoc network (SANET), has found a wide range of applications in providing ubiquitous wireless services. Despite its broad utility, the dynamic nature and lack of a centralized controller pose significant challenges to effective and flexible network management for xANET. Conventional network management protocols face challenges such as scalability, security vulnerabilities, configuration complexity, robustness, and performance resilience. Recent efforts have presented different approaches, focusing on policy-based network management (PBNM) and intent-driven network management (IDNM). However, there is no comprehensive survey to clarify their concepts and classifications. This paper presents a survey of the network management evolution for xANET, covering configuration-based, policy-based and the latest intent-driven approaches. We first introduce the characteristics and applications of xANET. Meanwhile, we investigate the network management concepts and challenges. Moreover, we survey the evolution of management protocols for xANET, including simple network management protocol (SNMP), PBNM, and IDNM. Then, we follow the detailed network management of xANET from configuration-based to policy-based and intent-driven approaches. Through comparative analysis, it is found that IDNM employs a more intelligent management protocol, demonstrating higher efficiency and flexibility in handling complex tasks and dynamic network management. This makes it better suited to addressing the challenges of xANET management. Finally, we summarize the remaining challenges and possible future research directions. © 2025 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

A robust incomplete large-scale group decision-making model for metaverse metro operations and maintenance

引用

Applied Soft Computing 2024年 156卷

作者： Bai, Wenhui Zhang, Chao Zhai, Yanhui Sangaiah, Arun Kumar School of Computer and Information Technology Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Shanxi Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Yunlin Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

The metaverse, constructed through digital technology, serves as a virtual realm intertwining with reality. Within this context, the challenge of evaluating data from diverse sources arises, and the application of large-scale group decision-making (LSGDM) methods emerges as a viable solution. Handling incomplete information and reducing dimensionality for large-scale decision-makers (DMs) is crucial in addressing complex decision-making problems. Moreover, addressing missing data is a fundamental and pivotal concern in tackling real-world decision challenges, given the ubiquitous presence of information gaps that cannot be straightforwardly integrated into decision models. Besides, the intricacies of LSGDM amplify this challenge by introducing a wealth of DMs, thereby augmenting the complexity and diversity of decision-related information. This paper proposes an approach to supplement missing data by double-dimensions. This paper explores various facets of similarity relationships within the data to enhance data completeness. Additionally, this paper categorizes DMs into clusters based on their relevance and establishes a two-stage consensus-reaching process (CRP) that takes into account both group sizes and individual consensus contributions. These CRPs play a crucial role in enhancing the overall consistency and consensus within the decision group. Subsequently, this paper applies a robust decision-making method rooted in MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the complete MULTIplicative form) to rank decision objects. Finally, this paper employs this proposed methodology in a practical case study that involves evaluating the operational status of a metaverse's urban construction metro system. Following these considerations, a comprehensive stability analysis of relevant parameters is conducted to guarantee the robustness and reliability of the decision-making process. © 2024 Elsevier B.V.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Printable Aligned Single-Walled Carbon Nanotube Film with Outstanding Thermal Conductivity and Electromagnetic Interference Shielding Performance

引用

Nano-Micro Letters 2022年第11期14卷 143-156页

作者： Zhihui Zeng Gang Wang Brendan F.Wolan Na Wu Changxian Wang Shanyu Zhao Shengying Yue Bin Li Weidong He Jiurong Liu Joseph W.Lyding Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationSchool of Materials Science and EngineeringShandong UniversityShandongJinan 250061People’s Republic of China Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Chemistry Swiss Federal Institute of Technology in Zurich(ETH Zürich)8092 ZurichSwitzerland School of Materials Science and Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore Empa Swiss Federal Laboratories for Materials Science and TechnologyÜberland Strasse 1298600 DübendorfSwitzerland Institute for Advanced Technology Shandong UniversityJinan 250061People’s Republic of China

Ultrathin,lightweight,and flexible aligned single-walled carbon nanotube(SWCNT)films are fabricated by a facile,environmentally friendly,and scalable printing *** aligned pattern and outstanding intrinsic properties render“metal-like”thermal conductivity of the SWCNT films,as well as excellent mechanical strength,flexibility,and ***,the aligned cellular microstructure promotes the electromagnetic interference(EMI)shielding ability of the SWCNTs,leading to excellent shielding effectiveness(SE)of~39 to 90 dB despite a density of only~0.6 g cm^(−3) at thicknesses of merely 1.5-24μm,*** ultrahigh thickness-specific SE of 25693 dB mm^(−1) and an unprecedented normalized specific SE of 428222 dB cm^(2)g^(−1) are accomplished by the freestanding SWCNT films,significantly surpassing previously reported shielding *** addition to an EMI SE greater than 54 dB in an ultra-broadband frequency range of around 400 GHz,the films demonstrate excellent EMI shielding stability and reliability when subjected to mechanical deformation,chemical(acid/alkali/organic solvent)corrosion,and high-/low-temperature *** novel printed SWCNT films offer significant potential for practical applications in the aerospace,defense,precision components,and smart wearable electronics industries.

关键词： Aligned film Single-walled carbon nanotube Lightweight Flexible Thermal conductivity Electromagnetic interference shielding

来源：评论

学校读者我要写书评

暂无评论

SweepEvGS: Event-Based 3D Gaussian Splatting for Macro and Micro Radiance Field Rendering from a Single Sweep

arXiv

引用

arXiv 2024年

作者： Wu, Jingqian Zhu, Shuo Wang, Chutian Shi, Boxin Lam, Edmund Y. Department of Electrical and Electronic Engineering The University of Hong Kong Pokfulam Hong Kong National Key Laboratory for Multimedia Information Processing and National Engineering Research Center of Visual Technology School of Computer Science Peking University Beijing100871 China

—Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However, conventional methods require high-frame-rate dense and high-quality sharp images, which are time-consuming and inefficient to capture, especially in dynamic environments. Event cameras, with their high temporal resolution and ability to capture asynchronous brightness changes, offer a promising alternative for more reliable scene reconstruction without motion blur. In this paper, we propose SweepEvGS, a novel hardware-integrated method that leverages event cameras for robust and accurate novel view synthesis across various imaging settings from a single sweep. SweepEvGS utilizes the initial static frame with dense event streams captured during a single camera sweep to effectively reconstruct detailed scene views. We also introduce different real-world hardware imaging systems for real-world data collection and evaluation for future research. We validate the robustness and efficiency of SweepEvGS through experiments in three different imaging settings: synthetic objects, real-world macro-level, and real-world micro-level view synthesis. Our results demonstrate that SweepEvGS surpasses existing methods in visual rendering quality, rendering speed, and computational efficiency, highlighting its potential for dynamic practical applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

来源：评论

学校读者我要写书评

暂无评论

Direct Multipath-Based SLAM

arXiv

引用

arXiv 2024年

作者： Liang, Mingchao Leitinger, Erik Meyer, Florian The Department of Electrical and Computer Engineering University of California La Jolla San DiegoCA92093 United States The Signal Processing and Speech Communication Laboratory Graz University of Technology Graz8010 Austria The Scripps Institution of Oceanography The Department of Electrical and Computer Engineering University of California La Jolla San DiegoCA92093 United States

In future wireless networks, the availability of information on the position of mobile agents and the propagation environment can enable new services and increase the throughput and robustness of communications. Multipath-based simultaneous localization and mapping (SLAM) aims at estimating the position of agents and reflecting features in the environment by exploiting the relationship between the local geometry and multipath components (MPCs) in received radio signals. Existing multipath-based SLAM methods preprocess received radio signals using a channel estimator. The channel estimator lowers the data rate by extracting a set of dispersion parameters for each MPC. These parameters are then used as measurements for SLAM. Bayesian estimation for multipath-based SLAM is facilitated by the lower data rate. However, due to finite resolution capabilities limited by signal bandwidth, channel estimation is prone to errors and MPC parameters may be extracted incorrectly and lead to a reduced SLAM performance. We propose a multipath-based SLAM approach that directly uses received radio signals as inputs. A new statistical model that can effectively be represented by a factor graph is introduced. The factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that avoids data preprocessing by a channel estimator. Numerical results based on synthetic and real data in challenging single-input, single-output (SISO) scenarios demonstrate that the proposed method outperforms conventional methods in terms of localization and mapping accuracy. Copyright © 2024, The Authors. All rights reserved.

关键词： Channel estimation

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：