检索结果-内蒙古大学图书馆

Graph-Based Representations in Pattern Recognition 1

丛书名： Lecture Notes in computer science

1000年

作者： Walter G. Kropatsch Nicole M. Artner Yll Haxhimusa Xiaoyi Jiang

ISBN: (数字)9783642382215

ISBN: (纸本)9783642382208

This book constitutes the refereed proceedings of the 9th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2013, held in Vienna, Austria, in May 2013. The 24 papers presented in this volume were carefully reviewed and selected from 27 submissions. They are organized in topical sections named: finding subregions in graphs; graph matching; classification; graph kernels; properties of graphs; topology; graph representations, segmentation and shape; and search in graphs.

关键词： Pattern Recognition Image processing and computer Vision computer Imaging, Vision, Pattern Recognition and Graphics computer Graphics Discrete Mathematics in computer science Data Structures

来源：评论

学校读者我要写书评

暂无评论

Artificial Neural Networks and Machine Learning – ICANN 2013 1

引用

丛书名： Lecture Notes in computer science

1000年

作者： Valeri Mladenov Petia Koprinkova-Hristova Günther Palm Alessandro E. P. Villa Bruno Appollini Nikola Kasabov

ISBN: (数字)9783642407284

ISBN: (纸本)9783642407277

The book constitutes the proceedings of the 23rd International Conference on Artificial Neural Networks, ICANN 2013, held in Sofia, Bulgaria, in September 2013. The 78 papers included in the proceedings were carefully reviewed and selected from 128 submissions. The focus of the papers is on following topics: neurofinance graphical network models, brain machine interfaces, evolutionary neural networks, neurodynamics, complex systems, neuroinformatics, neuroengineering, hybrid systems, computational biology, neural hardware, bioinspired embedded systems, and collective intelligence.

关键词： Artificial Intelligence Computation by Abstract Devices Algorithm Analysis and Problem Complexity Pattern Recognition Information Systems Applications (incl. Internet) Image processing and computer Vision

来源：评论

学校读者我要写书评

暂无评论

Spectral Interpretation of Decision Diagrams 1

引用

1000年

作者： Radomir S. Stanković Jaakko T. Astola

ISBN: (数字)9780387217345

ISBN: (纸本)9780387955452;9781475778731

Decision diagrams (DDs) are data structures for efficient (time/space) representations of large discrete functions. In addition to their wide application in engineering practice, DDs are now a standard part of many CAD systems for logic design and a basis for severe signal processing algorithms.;derives from attempts to classify and uniformly interpret DDs through spectral interpretation methods, relating them to different Fourier-series-like functional expressions for discrete functions and a group-theoretic approach to DD optimization. The book examines DDs found in literature and engineering practice and provides insights into relationships between DDs and different polynomial or spectral expressions for representation of discrete functions. In addition, it offers guidelines and criteria for selection of the most suitable representation in terms of space and time complexity. The work complements theory with numerous illustrative examples from practice. Moreover, the importance of DD representations to the verification and testing of arithmetic circuits is addressed, as well as problems related to various signal processing tasks.

关键词： Logic Design computer-Aided Engineering (CAD, CAE) and Design Register-Transfer-Level Implementation

来源：评论

学校读者我要写书评

暂无评论

GAHE: Geometry-Aware Embedding for Hyper-Relational Knowledge Graph Representation

引用

ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Zongsheng Cao Qianqian Xu Zhiyong Yang Yuan He Xiaochun Cao Qingming Huang State Key Laboratory of Information Security SKLOIS) Institute of Information Engineering Chinese Academy of Sciences China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China School of Computer Science and Technology University of Chinese Academy of Sciences China Security Department of Alibaba Group China School of Cyber Science and Technology Shenzhen Campus Sun Yat-sen University China

Knowledge graphs have proven highly effective for learning representations of entities and relations, with hyper-relational knowledge graphs (HKGs) gaining increased attention due to their enhanced representation capabilities. Each fact in an HKG consists of a main triple supplemented by attribute-value qualifiers that provide additional contextual information. Due to the complexity of hyper-relations, HKGs typically contain complex geometric structures, such as hierarchical, ring, and chain structures, often mixed together. However, previous work mainly embeds HKGs into Euclidean space, limiting their ability to capture these complex geometric structures simultaneously. To address this challenge, we propose a novel model called Geometry Aware Hyper-relational Embedding (GAHE). Specifically, GAHE adopts a multi-curvature geometry-aware approach by modeling HKGs in Euclidean space (zero curvature), hyperbolic space (negative curvature), and hyperspherical space (positive curvature) in a unified framework. In this way, it can integrate space-invariant and space-specific features to accurately capture the diverse structures in HKGs. In addition, GAHE introduces a module termed hyper-relational subspace learning, which allocates multiple sub-relations for each hyper-relation. It enables the exploitation of abundant latent semantic interactions and facilitates the exploration of fine-grained semantics between attribute-value pairs and hyper-relations across multiple subspaces. Furthermore, we provide theoretical guarantees that GAHE is fully expressive and capable of modeling a wide range of semantic patterns for hyper-relations. Empirical evaluations demonstrate that GAHE achieves state-of-the-art results on both hyper-relational and binary-relational benchmarks.

关键词： Knowledge Graph Hyper-relational Learning Multicurvature Spaces Geometry Aware

来源：评论

学校读者我要写书评

暂无评论

Visual Informatics: Bridging Research and Practice 1

引用

丛书名： Lecture Notes in computer science

1000年

作者： Halimah Badioze Zaman Peter Robinson Maria Petrou Patrick Olivier Heiko Schröder Timothy K. Shih

ISBN: (数字)9783642050367

ISBN: (纸本)9783642050350

Visual informatics is a field of interest not just among the information technology and computer science community, but also other related fields such as engineering, me- cal and health informatics and education starting in the early 1990s. Recently, the field is gaining more attention from researchers and industry. It has become a mul- disciplinary and trans-disciplinary field related to research areas such as computer vision, visualization, information visualization, real-time image processing, medical image processing, image information retrieval, virtual reality, augmented reality, - pressive visual mathematics, 3D graphics, multimedia-fusion, visual data mining, visual ontology, as well as services and visual culture. Various efforts has been - vested in different research, but operationally, many of these systems are not pro- nent in the mass market and thus knowledge and research on these phenomena within the mentioned areas need to be shared and disseminated. It is for this reason that the Visual Informatics Research Group from Universiti - bangsaan Malaysia (UKM) decided to spearhead this initiative to bring together experts in this very diversified but important research area so that more concerted efforts can be undertaken not just within the visual informatics community in Malaysia but from other parts of the world, namely, Asia, Europe, Oceania, and USA. This first International Visual Informatics Conference (IVIC 2009) was conducted collaboratively, by the visual informatics research community from the various public and private institutions of higher learning in Malaysia, and hosted by UKM.

关键词： Image processing and computer Vision Pattern Recognition computer Graphics Artificial Intelligence Algorithm Analysis and Problem Complexity User Interfaces and Human computer Interaction

来源：评论

学校读者我要写书评

暂无评论

Distributed Computing and Internet technology 1

引用

丛书名： Lecture Notes in computer science

1000年

作者： Chittaranjan Hota Pradip K. Srimani

ISBN: (数字)9783642360718

ISBN: (纸本)9783642360701

This book constitutes the refereed proceedings of the 9th International Conference on Distributed Computing and Internet technology, ICDCIT 2013, held in Bhubaneswar, India, in February 2013.;The 40 full papers presented together with 5 invited talks in this volume were carefully reviewed and selected from 164 submissions. The papers cover various research aspects in distributed computing, internet technology, computer networks, and machine learning.

关键词： computer Communication Networks Algorithm Analysis and Problem Complexity Information Storage and Retrieval Information Systems Applications (incl. Internet) Database Management Systems and Data Security

来源：评论

学校读者我要写书评

暂无评论

Digital Interaction and Machine Intelligence 1

引用

丛书名： Lecture Notes in Networks and Systems

1000年

作者： Cezary Biele Janusz Kacprzyk Jan W. Owsiński Wiesław Kopeć Andrzej Romanowski Marcin Sikorski

来源：评论

学校读者我要写书评

暂无评论

Image Analysis 1

引用

丛书名： Lecture Notes in computer science

1000年

作者： Joni-Kristian Kämäräinen Markus Koskela

ISBN: (数字)9783642388866

ISBN: (纸本)9783642388859

This book constitutes the refereed proceedings of the 18th Scandinavian Conference on Image Analysis, SCIA 2013, held in Espoo, Finland, in June 2013.;The 67 revised full papers presented were carefully reviewed and selected from 132 submissions. The papers are organized in topical sections on feature extraction and segmentation, pattern recognition and machine learning, medical and biomedical image analysis, faces and gestures, object and scene recognition, matching, registration, and alignment, 3D vision, color and multispectral image analysis, motion analysis, systems and applications, human-centered computing, and video and multimedia analysis.

关键词： Image processing and computer Vision Pattern Recognition Artificial Intelligence computer Graphics

来源：评论

学校读者我要写书评

暂无评论

Cross-Region Graph Convolutional Network with Periodicity Shift Adaptation for Wide-area SST Prediction

引用

ACM Transactions on Intelligent Systems and technology 1000年

作者： Han Peng Wengen Li Chang Jin Yichao Zhang Jihong Guan Hanchen Yang Shuigeng Zhou Department of Computer Science and Technology Tongji University China Department of Computer Science and Technology Tongji University China and Department of Computing The Hong Kong Polytechnic University China Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University China

Accurate prediction of sea surface temperature (SST) is of high importance in marine science, benefiting applications ranging from ecosystem protection to extreme weather forecasting and climate analysis. Wide-area SST usually shows diverse SST patterns in different sea areas due to the changes of temperature zones and the dynamics of ocean currents. However, existing studies on SST prediction often focus on small-area predictions and lack the consideration of diverse SST patterns. Furthermore, SST shows an annual periodicity, but the periodicity is not strictly adherent to an annual cycle. Existing SST prediction methods struggle to adapt to this non-strict periodicity. To address these two issues, we proposed the Cross-Region Graph Convolutional Network with Periodicity Shift Adaptation (RGCN-PSA) model which is equipped with the Cross-Region Graph Convolutional Network module and the Periodicity Shift Adaption module. The Cross-Region Graph Convolutional Network module enhances wide-area SST prediction by learning and incorporating diverse SST patterns. Meanwhile, the periodicity Shift Adaptation module accounts for the annual periodicity and enable the model to adapt to the possible temporal shift automatically. We conduct experiments on two real-world SST datasets, and the results demonstrate that our RGCN-PSA model obviously outperforms baseline models in terms of prediction accuracy. The code of RGCN-PSA model is available at https://***/ADMIS-TONGJI/RGCN-PSA/.

关键词： Wide-area SST prediction graph neural network diverse SST patterns periodicity shift adaptation

来源：评论

学校读者我要写书评

暂无评论

Efficient Low-Resource Medical Information processing Based on Semantic Analysis and Granular Computing

引用

ACM Transactions on Asian and Low-Resource Language Information processing 1000年

作者： Yuting Cheng Chao Zhang Arun Kumar Sangaiah Xueqing Fan Anna Wang Liyin Wang Yixin Liu School of Computer and Information Technology Shanxi University China School of Computer and Information Technology Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Taiwan and Department of Electrical and Computer Engineering Lebanese American University Lebanon Chumin College Shanxi University China

The rise of the digital economy and e-commerce has fostered a movement towards efficient low-resource medical information processing, a trend that holds great importance in the healthcare sector. Diabetes, being a widespread chronic condition, has witnessed the introduction of glucometers, which offer patients a convenient method of monitoring their blood sugar levels. However, it is worth noting that a considerable proportion of online comments may be subject to emotional bias or contain inaccurate information. Furthermore, the performance of glucometers can be influenced by several attributes, including price, accuracy and portability, thereby potentially complicating the decision-making process for consumers. Semantic analysis can be employed to acquire valuable information, aiding consumers in reasonably choosing the suitable glucometer. This paper utilizes the benefits of granular computing, an emerging computing paradigm, to effectively handle incomplete and uncertain medical information. It employs generalized fuzzy sets, rough sets and three-way decisions (TWD) techniques to boost the accuracy and reliability of medical information fusion. Subsequently, the MABAC (Multi-Attribute Border Approximation Area Comparison) method is utilized to evaluate the reviews of every glucometer, calculate their aggregated scores, and rank and compare them. Ultimately, in light of consumers’ needs and trade-offs, the glucometer with the highest score can be selected. The proposed approach comprehensively considers the weight and priority of multiple attributes, reduces information overload and mitigates selection difficulties, thereby enhancing the accuracy and reliability of low-resource medical information processing.

关键词： Semantic analysis granular computing medical information processing three-way decision

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：