149 resources related to Cloud Visualization
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- Most published Xplore authors for Cloud Visualization
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
All fields of satellite, airborne and ground remote sensing.
OCEANS 2020 - SINGAPORE
An OCEANS conference is a major forum for scientists, engineers, and end-users throughout the world to present and discuss the latest research results, ideas, developments, and applications in all areas of oceanic science and engineering. Each conference has a specific theme chosen by the conference technical program committee. All papers presented at the conference are subsequently archived in the IEEE Xplore online database. The OCEANS conference comprises a scientific program with oral and poster presentations, and a state of the art exhibition in the field of ocean engineering and marine technology. In addition, each conference can have tutorials, workshops, panel discussions, technical tours, awards ceremonies, receptions, and other professional and social activities.
Cluster Computing, Grid Computing, Edge Computing, Cloud Computing, Parallel Computing, Distributed Computing
The aim of INES conference series is to provide researchers and practitioners from industry and academia with a platform to report on recent developments in the area of computational intelligence.
IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.
The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...
Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...
Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.
Proceedings of 2012 International Conference on Measurement, Information and Control, 2012
Build a "Point Cloud Pyramid" data model similar to the image pyramid by analyzing the mass LIDAR point cloud data and image data in common and learning image pyramid data model and its construction method; Create the data model by rarefy and blocking the mass point cloud. Then construct a quadtree spatial index and figure out a quadtree searching method ...
2015 IEEE 3rd Working Conference on Software Visualization (VISSOFT), 2015
Version control repositories contain a wealth of implicit information that can be used to answer many questions about a project's development process. However, this information is not directly accessible in the version control archives and must be extracted and visualized. This paper describes ConceptCloud, a flexible, interactive browser for SVN and Git repositories. The main novelty of our approach is ...
2018 International Conference on 3D Immersion (IC3D), 2018
The growing availability of RGB-D data, as delivered by current depth sensing devices, forms the basis for a variety of mixed reality (MR) applications, in which real and synthetic scene content is combined for interaction in real- time. The processing of dynamic point clouds with possible fast and unconstrained movement poses special challenges to the surface reconstruction and rendering algorithms. ...
2009 International Conference on Advances in Social Network Analysis and Mining, 2009
Social tagging systems are becoming an interesting way to retrieve web information from previously annotated data. These sites present a tag cloud made up by the most popular tags, where neither tag grouping nor their corresponding content is considered. We present a methodology to obtain and visualize a cloud of related tags based on the use of self-organizing maps, and ...
2010 IEEE Pacific Visualization Symposium (PacificVis), 2010
In this paper, we introduce a visualization method that couples a trend chart with word clouds to illustrate temporal content evolutions in a set of documents. Specifically, we use a trend chart to encode the overall semantic evolution of document content over time. In our work, semantic evolution of a document collection is modeled by varied significance of document content, ...
Augmented Reality in Operating Rooms
Cloud Ecosystem: A View from the IEEE Cloud Congress @ GlobeCom 2012
Emerging Standards in Cloud Computing
Cloud Computing for Emerging Markets Preview
"A View from the Cloud" -- IEEE Cloud 2012 Conference
Networking in the Cloud Computing Era
Cloud Standardization: A View from IEEE Cloud Congress @ GlobeCom 2012
Joe Weinman Sr. VP, TelX
IEEE Corporate Innovation Award - Pixar Animation Studios - 2018 IEEE Honors Ceremony
IEEE Top Trends for 2012 at CES: Cloud-Based Applications
IEEE Cloud Computing for Emerging Markets: Buyya
Big Data & the Cloud: Privacy and Security issues
Lew Tucker, IEEE GLOBECOM'13 Keynote Address - Lew Tucker, CTO, Cisco Systems
IEEE Cloud Computing for Emerging Markets: Pitroda
IEEE Cloud Computing for Emerging Markets: Gonzalez-Velez
Big Data & the Cloud: The Road Ahead
VMware CEO Pat Gelsinger on Innovation: Changing the World Changing Business - 2016 Women in Engineering Conference
Tech News on IEEE.tv June 2012 Edition
Cafe: Cloud Appliances for Enterprises
Build a "Point Cloud Pyramid" data model similar to the image pyramid by analyzing the mass LIDAR point cloud data and image data in common and learning image pyramid data model and its construction method; Create the data model by rarefy and blocking the mass point cloud. Then construct a quadtree spatial index and figure out a quadtree searching method to achieve the purpose of mass point cloud visualization by dynamic reading and displaying base on the spatial location and scale. Finally, realized this method and proved its feasibility.
Version control repositories contain a wealth of implicit information that can be used to answer many questions about a project's development process. However, this information is not directly accessible in the version control archives and must be extracted and visualized. This paper describes ConceptCloud, a flexible, interactive browser for SVN and Git repositories. The main novelty of our approach is the combination of an intuitive tag cloud visualization with an underlying concept lattice that provides a formal structure for navigation. ConceptCloud supports concurrent navigation in multiple linked but individually customizable tag clouds, which allows for multi-faceted repository browsing and for the construction of unique visualizations. We describe the mathematical foundations and implementation of our approach, and use ConceptCloud to quickly gain insight into the team structure and development process of two projects.
The growing availability of RGB-D data, as delivered by current depth sensing devices, forms the basis for a variety of mixed reality (MR) applications, in which real and synthetic scene content is combined for interaction in real- time. The processing of dynamic point clouds with possible fast and unconstrained movement poses special challenges to the surface reconstruction and rendering algorithms. We propose an end-to-end system for dynamic point cloud visualization from RGB-D input data that takes advantage of the Unity3D game engine for efficient state-of-the-art rendering and platform- independence. We discuss specific requirements and key components of the overall system along with selected aspects of its implementation. Our experimental evaluation demonstrates that high-quality and versatile visualization results can be obtained for datasets of up to 5 million points in real-time.
Social tagging systems are becoming an interesting way to retrieve web information from previously annotated data. These sites present a tag cloud made up by the most popular tags, where neither tag grouping nor their corresponding content is considered. We present a methodology to obtain and visualize a cloud of related tags based on the use of self-organizing maps, and where the relations among tags are established taking into account the textual content of tagged documents. Each map unit can be represented by the most relevant terms of the tags it contains, so that it is possible to study and analyze the groups as well as to visualize and navigate through the relevant terms and tags.
In this paper, we introduce a visualization method that couples a trend chart with word clouds to illustrate temporal content evolutions in a set of documents. Specifically, we use a trend chart to encode the overall semantic evolution of document content over time. In our work, semantic evolution of a document collection is modeled by varied significance of document content, represented by a set of representative keywords, at different time points. At each time point, we also use a word cloud to depict the representative keywords. Since the words in a word cloud may vary one from another over time (e.g., words with increased importance), we use geometry meshes and an adaptive force-directed model to lay out word clouds to highlight the word differences between any two subsequent word clouds. Our method also ensures semantic coherence and spatial stability of word clouds over time. Our work is embodied in an interactive visual analysis system that helps users to perform text analysis and derive insights from a large collection of documents. Our preliminary evaluation demonstrates the usefulness and usability of our work.
The proposed method uses context-preserving, dynamic word clouds to illustrate content evolution. It generates a sequence of word clouds in which related words are grouped together. This sequence is then coupled with a trend chart that summarizes content changes so that users can better explore large collections of documents.
Tag cloud is an efficient visualization technique to help users rapidly understand the significant components within a tag based dataset. To make practical use of the visualization method, we proposed a cross-comparison mechanism for discovering Simple Sequence Repeat (SSR) biomarkers by annotating retrieved tag entries in various colors and font sizes to differentiate conservative status of two species groups. The identified SSR tag entries can represent the conservative and exclusive features among various species with respect to a specified functional gene set. Grouped SSR features of the same kind species can be classified and displayed simultaneously in order to compare evolutionary relationships. In addition, we applied different parameter settings for SSR discovery algorithms to generate multiscale tag clouds which provide different levels of significance of discovered repeat segments. In this study, several significant SSR patterns within eight skeletal development genes from 10 different species were illustrated and classified as notable features for the previously defined two groups of mammalian and fishery species. The proposed multiscale SSR tag clouds were demonstrated to be able to facilitate biologists on searching notable SSR biomarkers or putative gene regulatory elements in this study.
In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high- quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets.
Word clouds provide a simple and effective means to visually communicate the most frequent words of text documents. However, only few word cloud visualizations support the contrastive analysis of multiple texts. This paper introduces Concentri Cloud, a layered word cloud layout that merges the words from several text documents into a single visualization. The weighted words are arranged in a concentric layout, with those representing the individual documents on the outer circle and the merged ones on inner circles. Interaction techniques allow to analyze the word cloud composition and to provide details on demand. The approach has been implemented and tested on several examples. A qualitative evaluation indicates the general value of Concentri Cloud and reveals benefits and limitations.
With the fast growing volume of 3D point-cloud data, innovative point-cloud visualization techniques are in need for efficient and accurate information presentation and navigation. In this paper, we propose a hierarchical RBF based approach to interactively visualize 3D point-cloud. With this approach users are able to achieve better resolution in a Region of Interest(ROI) without having to transmit and render the entire object in high detail.
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