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检索条件"任意字段=Conference on Information Visualization Theory and Applications"

共 1067 条记录，以下是11-20 订阅

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Research and Analysis of the Green Vision Rate of Street Space Based on information visualization Technology 7th

Research and Analysis of the Green Vision Rate of Street Spa...

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7th International conference on Wireless Communications, Networking and applications, WCNA 2023

作者： Wang, Jun Zhang, Hua Yan, Zhulong Art School Huzhou University Huzhou China

ISBN: (纸本)9789819624089

Taking the research results of China National Knowledge Network (CNKI) from 1998 to 2023 as the data source, with the help of CiteSpace V and VOSviewer digital technology, the knowledge map on the research of China street space is drawn. The visualization technology shows the structure, evolution of street space, and the interrelationship of green vision rate research, and intuitively shows the research hotspot and frontier dynamics of green vision rate of street space in China. Research has learned that before 2017, the green vision rate of street space was in the bud, and then began to develop rapidly. At present, the street space green rate is mainly concentrated in the street roaming, street walkability, measurement method, evaluation index, healing environment, restorative environment, public space security, street image research, VR virtual reality research and green rate, green rate, green rate, etc. Through the visual map analysis of the green vision rate literature in the street space, it shows that the use of new technologies and cross-field integration will become the future research trend. © The Author(s) 2025.

关键词： date visualization development trend green visual index street space

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Microwave Photonics Computational Signal Algebra Framework for Radar Integrated Sensing and Communication applications 5

Microwave Photonics Computational Signal Algebra Framework f...

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5th IEEE MTT-S Latin America Microwave conference, LAMC 2025

作者： Aceros, Cesar Valera-Marquez, Juan Aviles, Yvonne Rodriguez, Domingo UTS Santander Colombia Universidad de Puerto Rico Río Piedras Puerto Rico Universidad de Puerto Rico Mayagüez Puerto Rico

ISBN: (纸本)9798331540401

This work presents a computational signal algebra (CSA) framework for microwave photonics signal processing efforts in radar integrated sensing and communication (RISC) applications, for areas such as parameter estimation, beamforming, and waveform design. The proposed framework presents a set of computational methods, with an associated visualization environment for time-frequency tools such as the short-time Fourier transform (STFT), the cross-ambiguity function (CAF), and the Wigner-Ville distribution (WVD). The discrete ambiguity function (DAF) was implemented as a user defined function (UDF) to be used as a signal correlation analysis and waveform design tool aiming at assisting in research efforts towards efficient use of the electromagnetic spectrum by reducing noise and interference and adhering to spectrum management regulatory standards. Significant computational speedups were obtained for the CAF by introducing novel data sampling algorithmic techniques. Finally, an information flow security framework is proposed utilizing a post-quantum cryptography (PQC) approach in RISC environments. © 2025 IEEE.

关键词： Wigner-Ville distribution

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A Web-Based Platform for Women Crime Data visualization and Analysis 12th

A Web-Based Platform for Women Crime Data Visualization and ...

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12th International conference on Frontiers of Intelligent Computing: theory and applications, FICTA 2024

作者： Anvesh, Kachi Swapna, N. Prashanth, S.K. Farooqui, Maryam Fatima Habeeb, Novera Department of Information Technology Vardhaman College of Engineering Telangana Hyderabad501218 India Department of Computer Science and Engineering Vijay Rural Engineering College Telangana Nizamabad503003 India Department of Information Technology Vasavi College of Engineering Telangana Hyderabad500031 India Department of Computer Science and Engineering J.B. Institute of Engineering & Technology Telangana Hyderabad500075 India

ISBN: (纸本)9789819601387

A web-based platform created with Python, HTML, and CSS intended to offer useful crime data visualization for a particular city. Users of the platform can learn about crime patterns and trends through interactive visualizations because of the program’s usage of Python. An intuitive and user-friendly front-end interface was primarily created using HTML and CSS. Through a web browser, users can access the platform and study crime data and engage with different visualizations. Python is used to create the crime Vs back end, which is essential for producing graphical representations based on crime data. Data collection, preprocessing, storage, and graphical representation are a few of the crucial elements involved in the development of crime rate Vs. crime statistics are gathered from trustworthy sources like law enforcement organizations and public records. Python is employed for transforming it into a suitable format for visualization. A database is used to store the processed data, making it easy to access it for graphical depiction. Gives users access to an appealing and interactive environment that was created using HTML and CSS. Users can personalize their views, filter data-based on crime types or time periods, and visualize crime incidents using a variety of graphical tools, including bar charts, pie charts, and heat maps. Users can use the visualizations to find patterns, hot spots, and trends in crime data, improving the understanding of crime processes. A Web site that targets high-crime states in India aims to inform women about crime rates and support law enforcement. It provides graphical statistics on trafficking, sexual assault, and other topics, allowing for educated safety measures and emphasizing the necessity of addressing underlying problems to create a safer atmosphere. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： HTML

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Air Quality Data Integration and visualization in Urban Environment 12th

Air Quality Data Integration and Visualization in Urban Envi...

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12th International conference on Frontiers of Intelligent Computing: theory and applications, FICTA 2024

作者： Sowinski-Mydlarz, Viktor Vassilev, Vassil Gasiorowski, Pawel GATE Institute Sofia University "St. Kliment Ohridski" Sofia Bulgaria Cyber Security Research Centre London Metropolitan University London United Kingdom

ISBN: (纸本)9789819601424

Monitoring air pollution in urban areas is crucial for safeguarding public health and environmental well-being. The proper integration and visualization of air quality data in extensive urban platforms enabling user interaction are important for gaining valuable insights and making informed decisions about measures to mitigate the problem. This paper proposes an air quality platform, bridging the gap between scientific data and the general audience. It promotes an enhanced understanding and prevention of air pollution. A comprehensive data pipeline is designed to efficiently collect, store, and visualize air quality data in Sofia, Bulgaria. Leveraging open-source technologies like QGIS, MongoDB, Flask, and Cesium Ion, the platform integrates data from 23 air quality stations onto a terrain map and 3D building layer. The paper addresses challenges in data processing, ensuring accuracy, managing high volumes, and effectively communicating complex information. The scalability, transparency, and accessibility of the proposed approach offer significant contributions to environmental monitoring. Additionally, integrating triangulation of measurements enhances the platform’s capabilities, facilitating informed decision-making and supporting sustainable urban development initiatives. The paper concludes with insights into future enhancements, including visualization of CFD simulations of airflow in urban context, promising advancements in understanding urban air quality dynamics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Environmental monitoring

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visualization of Multilayer Networks 4th

Visualization of Multilayer Networks

引用

4th International conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Lazzaro, Ilaria Milano, Marianna Department of Medical and Surgical Sciences University "Magna Græcia" Catanzaro88100 Italy Department of Experimental and Clinical Medicine University Magna Græcia Catanzaro88100 Italy

ISBN: (纸本)9783031812460

Network theory, in particular complex networks, has undergone considerable development finding its way into many real-world applications. However, they have several different types of relationships that cannot be represented by a mono layer network [11]. In fact, multilayer networks explicitly incorporate multiple channels, creating the right context to describe interconnected systems through different related layers, where nodes are the entities of the system and the edges represent the interactions between them. The application fields that may be modelled by multilayer networks range from human and social systems [8], to technological and transport systems, including biology and medicine [4]. Although various approaches for the visualization of multilayer networks have been suggested in recent years, this is an evolving field. In this work, we present an overview of the tools exploited for the visualization of multilayer networks. Then, we present a comparison among different tools through a case study represented by a real multilayer network. The network under investigation is a multilayer network composed of 8, 392 nodes and 128, 199 edges distributed over 2 layer that relate disease and drug. We propose methods for visualisation of the network that provide a topological analysis, attempting to derive the main measurement metrics. Through the visualisation carried out on the dataset, we will attempt to demonstrate the different layout configurations that a network can assume and the parameters that can be associated to each tool used in order to derive real scientific information. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Multilayer neural networks

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Hotspots and Frontiers on Copper Mineral Prediction Using Knowledge Graph 3

Hotspots and Frontiers on Copper Mineral Prediction Using Kn...

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3rd International conference on Electrical, Electronics, and information Engineering, EEIE 2024

作者： An, Zhaofeng Wang, Yongzhi Dong, Yuhao Tian, Jiangtao Wang, Cheng Bilal, Muhammad Atif College of Geoexploration Science & Technology Jilin University Changchun130061 China Institute of Integrated Information for Mineral Resources Prediction Jilin University Changchun130061 China Geological Survey Institute of Xinjiang Uygur Autonomous Region Urumqi83000 China

ISBN: (纸本)9781510688179

Copper mineral is a critical industrial raw material that is essential to global economic development. To explore the research status, hotspots, and frontiers in the field of copper mineral prediction, 472 Chinese articles and 152 English articles published between 1974 and 2024 were collected from the CNKI and Web of Science WoS core databases. Using the community structure analysis software CiteSpace, a visualization analysis was conducted on aspects such as collaborative authorship, research countries, research institutions, keyword clustering, and spatiotemporal keyword distribution maps. The results reveal an evolutionary trend in copper mineral prediction research from fundamental theory to technical applications: early studies focused primarily on basic issues such as metallogenic conditions, metallogenic processes, and geochemical anomalies, while recent studies have gradually shifted toward the application of intelligent technologies such as predictive models, deep mineral exploration, and spatial data analysis. Domestic research emphasizes resource development and precise prediction in specific regions, whereas international research focuses more on the introduction and promotion of intelligent methods. In the future, technologies such as data mining, machine learning, and 3D modeling are expected to further advance the efficient exploration and development of copper mineral resources This study provides an important reference for understanding research dynamics and directions in the field of copper mineral prediction. © The Authors.

关键词： Prediction models

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Bridging the Machine-Human Gap in Blurred-Image Classification via Entropy Maximisation

Bridging the Machine-Human Gap in Blurred-Image Classificati...

引用

International Image Processing, applications and Systems conference (IPAS)

作者： Emilio Sansano-Sansano Marina Martínez-García Javier Portilla INIT Universitat Jaume I Castellón de la Plana Spain IMAC Universitat Jaume I Castellón de la Plana Spain Instituto de Óptica CSIC Madrid Spain

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Recent studies point to an accuracy gap between humans and Artificial Neural Network (ANN) models when classifying blurred images, with humans outperforming ANNs. To bridge this gap, we introduce a spectral channel-based range-constrained entropy merit function, from which we devise a zero-phase, circular symmetric blind deblurring method. We apply it as a pre-processing step for image classification and test it using pre-trained classification models and images blurred by Gaussian kernels. We compare our method to state-of-the-art restoration methods, showing its superiority, effectively bridging the machine-human gap for most models and blur levels. Our results also rank higher than the competitors in no-reference and full-reference image quality metrics. Notwithstanding the limitation to zero-phase blur, this work shows that, for image pre-processing aimed at visual tasks, it may be advantageous to use merit functions based on vision science and information theory, rather than on the expected error to the latent image.

关键词： Measurement Image quality visualization Computer vision Artificial neural networks Entropy Kernel Optimization information theory Image classification

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Microwave Photonics Computational Signal Algebra Framework for Radar Integrated Sensing and Communication applications

Microwave Photonics Computational Signal Algebra Framework f...

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IEEE MTT-S Latin America Microwave conference (LAMC)

作者： Cesar Aceros Juan Valera-Marquez Yvonne Aviles Domingo Rodriguez UTS Santander Colombia Universidad de Puerto Rico Río Piedras Universidad de Puerto Rico Mayagüez

ISBN: (数字)9798331540401

ISBN: (纸本)9798331540418

关键词： Microwave measurement Reduced instruction set computing Radar measurements Algebra Microwave communication Microwave theory and techniques Integrated sensing and communication Radar signal processing Cryptography Microwave photonics

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Mitigating Data Sparsity in Point-of-Interest Recommendation Systems Using Multi-Modal User Profiles

Mitigating Data Sparsity in Point-of-Interest Recommendation...

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International ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI-NCON)

作者： Sudarat Arthan Kreangsak Tamee Department of Computer Science and Information Technology Naresuan University Phitsanulok Thailand Department of Computer Science and Information Technology Naresuan University Research Center for Academic Excellence in Nonlinear Analysis and Optimization Naresuan University Phitsanulok Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This study presents a solution to the data sparsity issue in POI recommendation systems by introducing a multi-modal user profile approach called Visual-Textual Collaborative Filtering (VTCF). VTCF integrates textual POI descriptions from Wikipedia with user-generated photos to improve the representation of user preferences. Using publicly available geo-tagged photo datasets, we compared VTCF with various baseline methods, including traditional user-based collaborative filtering and approaches based on visual and contextual preferences. The experimental results demonstrate that our approach successfully addresses the challenges of sparse check-in data, resulting in more accurate and relevant recommendations. The findings suggest that VTCF is a promising method for improving recommendation accuracy. Future work could explore additional data sources and techniques to further enhance POI recommendation systems. Moreover, computational trade-offs and scalability should be considered, as integrating textual and visual data adds system complexity. Strategies such as batch processing and parallel computation could help mitigate these issues for large-scale applications.

关键词： visualization Accuracy Collaborative filtering Soft sensors Scalability Batch production systems Robustness Complexity theory Resource management Recommender systems

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PCAD: A Real-World Dataset for 6D Pose Industrial Anomaly Detection

PCAD: A Real-World Dataset for 6D Pose Industrial Anomaly De...

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IEEE Winter applications and Computer Vision Workshops (WACVW)

作者： Robert Maack Lars Thun Thomas Liang Hasan Tercan Tobias Meisen Institute for TMDT University of Wuppertal University of Wisconsin-Madison

ISBN: (数字)9798331536626

ISBN: (纸本)9798331536633

In industrial assembly line manufacturing, visual inspection is crucial for maintaining high-quality standards. The detection of defects can be accomplished using anomaly detection, by identifying irregularities in RGB images. However, currently available datasets mostly contain only poseinvariant samples. Lately, this has resulted in the emergence of datasets that supplement depth information into RGB image data, enabling defect detection with respect to the geometrical surface of objects. Nevertheless, the acquisition costs for high-resolution 3D point cloud data are considerably higher than the costs of conventional RGB cameras. Other datasets contain only synthetic 3D representations of the objects for model training. However, this results in a considerable gap in the applicability of real-world industrial applications. Conversely, multi-component CAD models are already an abundantly available source of 3D information, yet, not fully leveraged for anomaly detection. In this paper, we introduce the dataset PCAD - a dataset acquired using a specialized hardware setup designed to capture high-quality images of assembly groups with varying complexity and different poses in a systematic and reproducible way. The dataset includes variations in structural and semantic anomalies, poses, and lighting conditions, providing a comprehensive real-world scenario for defect detection. We show the usability and efficacy of our dataset regarding various state-of-the-art anomaly detection models. Furthermore, we demonstrate its applicability to visual quality inspection and its potential to support future research in this field. The code and dataset are publicly available: https://***/tmdt-buw/pcad-dataset

关键词： Solid modeling visualization Three-dimensional displays Costs Lighting Inspection Complexity theory Anomaly detection Assembly Defect detection

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