IEEE Computer Graphics and Applications最新文献_第10页

IEEE Annals of the History of Computing 电气和电子工程师学会计算机史年鉴

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/mcg.2023.3348703

引用次数: 0

Panoramic Ray Tracing for Interactive Mixed Reality Rendering Based on 360° RGBD Video. 基于360°RGBD视频的交互式混合现实渲染全景光线跟踪。

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 Epub Date: 2024-01-25 DOI: 10.1109/MCG.2023.3327383

Jian Wu, Lili Wang

引用次数: 0

Interactive Visualization in Applications 应用中的交互式可视化

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/mcg.2023.3331295

C. Gillmann, Johanna Schmidt, Daniel Wiegreffe

引用次数: 0

New Insights in Smooth Occluding Contours for Nonphotorealistic Rendering. 非逼真渲染中平滑遮挡轮廓的新见解

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/MCG.2023.3338784

Aaron Hertzmann, Rajesh Sharma

引用次数: 0

Using Counterfactuals to Improve Causal Inferences From Visualizations. 利用反事实改进可视化的因果推断。

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/MCG.2023.3338788

David Borland, Arran Zeyu Wang, David Gotz, Theresa-Marie Rhyne

{"title":"Using Counterfactuals to Improve Causal Inferences From Visualizations.","authors":"David Borland, Arran Zeyu Wang, David Gotz, Theresa-Marie Rhyne","doi":"10.1109/MCG.2023.3338788","DOIUrl":"https://doi.org/10.1109/MCG.2023.3338788","url":null,"abstract":"Traditional approaches to data visualization have often focused on comparing different subsets of data, and this is reflected in the many techniques developed and evaluated over the years for visual comparison. Similarly, common workflows for exploratory visualization are built upon the idea of users interactively applying various filter and grouping mechanisms in search of new insights. This paradigm has proven effective at helping users identify correlations between variables that can inform thinking and decision-making. However, recent studies show that consumers of visualizations often draw causal conclusions even when not supported by the data. Motivated by these observations, this article highlights recent advances from a growing community of researchers exploring methods that aim to directly support visual causal inference. However, many of these approaches have their own limitations, which limit their use in many real-world scenarios. This article, therefore, also outlines a set of key open challenges and corresponding priorities for new research to advance the state of the art in visual causal inference.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139565424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Computer Society D&I Fund 电气和电子工程师学会计算机协会 D&I 基金

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/mcg.2023.3348728

引用次数: 0

ComputingEdge ComputingEdge

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2024-01-01 DOI: 10.1109/mcg.2023.3348730

引用次数: 0

LayerNet: A One-Step Layered Network for Semantic Segmentation at Night. LayerNet:一种用于夜间语义分割的一步分层网络。

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2023-11-01 Epub Date: 2023-11-06 DOI: 10.1109/MCG.2023.3253167

Hao Li, Changjiang Liu, Yang Yang

引用次数: 1

Quantum Computing and Visualization: A Disruptive Technological Change Ahead. 量子计算与可视化：未来的颠覆性技术变革。

IF 1.8 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2023-11-01 DOI: 10.1109/MCG.2023.3316932

E Wes Bethel, Mercy G Amankwah, Jan Balewski, Roel Van Beeumen, Daan Camps, Daniel Huang, Talita Perciano, Theresa-Marie Rhyne

{"title":"Quantum Computing and Visualization: A Disruptive Technological Change Ahead.","authors":"E Wes Bethel, Mercy G Amankwah, Jan Balewski, Roel Van Beeumen, Daan Camps, Daniel Huang, Talita Perciano, Theresa-Marie Rhyne","doi":"10.1109/MCG.2023.3316932","DOIUrl":"https://doi.org/10.1109/MCG.2023.3316932","url":null,"abstract":"The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore's Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. While present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71489170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Call for Papers: IEEE Computer Graphics and Applications 论文征集:IEEE计算机图形学与应用

4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2023-11-01 DOI: 10.1109/mcg.2023.3316908

引用次数: 0