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检索条件"任意字段=IEEE Symposium on Large Data Analysis and Visualization"

共 15522 条记录，以下是221-230 订阅

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Using Underwater Hyperspectral Imaging to Increase Feature Detection and Improve Under-Ice Navigation

Using Underwater Hyperspectral Imaging to Increase Feature D...

引用

International symposium on Underwater Technology

作者： Leonard Günzel Janina Osanen Håvard Snefjellå Løvås Geir Johnsen Alberto García Ortiz Martin Ludvigsen Marine Technology NTNU Trondheim Norway Marine Biology NTNU Trondheim Norway Integrated Digital Systems University of Bremen Bremen Germany

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

Extensive sea ice in Arctic marine regions has hindered indepth exploration and research. To overcome this frontier, underwater robots are increasingly used to explore beneath the ice cover. While this enables research over a broader area, it increases the risk of losing valuable vehicles under the ice, placing greater emphasis on the navigational capabilities of the robots. While inertial and acoustical navigation methods share limitations for operating under the ice, visual navigation can utilize optical features for position estimation at a very fine resolution. However, the underside of ice tends to lack visible features. To overcome this, we propose integrating a novel Underwater Hyperspectral Imager. This technology captures detailed spectral information, revealing features and patterns invisible to traditional imaging methods. To test this, a Remotely Operated Vehicle was equipped with an upward-pointing hyperspectral imager. Three Arctic expeditions were conducted, capturing under-ice data including an Arctic ice algae bloom. To determine whether the hyperspectral imager provides improved navigation capabilities, we created five spectral transformations utilizing the spectral quantity of the hyperspectral domain by either increasing the number of layers fed into the detection algorithm (5-Band, 10-Band and 20-band) or by transforming the spectra using Principal Component analysis (PCA) and the Pearson correlation. We then compared these to four transformations which resembled the behaviour of an RGB/grayscale equivalent. We found that the hyperspectral methods showed an improvement in precision. These improvements in precision highlight the potential of hyperspectral imagina for robust navigation in challenging under-ice environments.

关键词： Integrated optics visualization Navigation Feature detection Estimation Gray-scale Optical imaging Arctic Hyperspectral imaging Principal component analysis

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Advanced Aggregate Computation for large data visualization 5

Advanced Aggregate Computation for Large Data Visualization

引用

ieee 5th symposium on large data analysis and visualization (LDAV)

作者： Li, Xinxiao Kuroda, Akira Matsuzaki, Hidenori Nakajima, Nobuyasu Toshiba Co Ltd Tokyo Japan

ISBN: (纸本)9781467385176

large data visualization and analysis faces challenges related to performance, operability, degree of discrimination, etc.. In this paper, an advanced aggregate computation is proposed to solve these issues from three aspects. By virtue of visualization-based data separation and aggregation, a large dataset is mapped to a visualization-based small dataset for efficient visualization while keeping operability of data. A minimum size of visual primitives for aggregated data is defined to ensure visibility of important but tiny information. And a D3-based rendering implementation improves the performance of consecutive visualizations.

关键词： visualization analysis visual primitives consecutive visualizations aggregate computation

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ADR visualization: A Generalized Framework for Ranking large-Scale Scientific data using analysis-Driven Refinement 4

ADR Visualization: A Generalized Framework for Ranking Large...

引用

ieee symposium on large data analysis and visualization

作者： Nouanesengsy, Boonthanome Woodring, Jonathan Patchett, John Myers, Kary Ahrens, James Los Alamos Natl Lab Los Alamos NM 87544 USA

ISBN: (纸本)9781479952151

Prioritization of data is necessary for managing large-scale scientific data, as the scale of the data implies that there are only enough resources available to process a limited subset of the data. For example, data prioritization is used during in situ triage to scale with bandwidth bottlenecks, and used during focus+context visualization to save time during analysis by guiding the user to important information. In this paper, we present ADR visualization, a generalized analysis framework for ranking large-scale data using analysis -Driven Refinement (ADR), which is inspired by Adaptive Mesh Refinement (AMR). A large-scale data set is partitioned in space, time, and variable, using user-defined importance measurements for prioritization. This process creates a prioritization tree over the data set. Using this tree, selection methods can generate sparse data products for analysis, such as focus+context visualizations or sparse data sets.

关键词： data triage focus plus context large-scale data big data scientific data prioritization adaptive mesh refinement I.3.1 [Computer Graphics]: Hardware Architecture-Parallel processing I.3.3 [Computer Graphics]: Picture/Image Generation-Viewing algorithms

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Lossy Compression for visualization of Atmospheric data 11

Lossy Compression for Visualization of Atmospheric Data

引用

ieee 11th symposium on large data analysis and visualization (LDAV)

作者： Semeraro, Dave Orf, Leigh Texas Adv Comp Ctr Austin TX 78758 USA Univ Wisconsin Madison WI USA

ISBN: (纸本)9781665432832

Lossy compression is a data compression technique that sacrifices precision for the sake of higher compression rates. While loss of precision is unacceptable when storing simulation data for check pointing, it has little discernable impact on visualization. Saving simulation output for later examination is still a prevalent workflow. Domain scientists often return to data from older runs to examine the data in a new context. Storage of visualization data at full precision is not necessary for this purpose. The use of lossy compression can therefore relieve the pressure on HPC storage equipment or be used to store data at higher temporal resolution than without compression. In this poster we show how lossy compression was used to store visualization data for the analysis of a supercell thunderstorm. The visual results will be shown as well as details of how the compression was used in the workflow.

关键词： data Compression Atmospheric science

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Method for Improving RadViz's Navigation Function Based on Focusing and Filtering 8

Method for Improving RadViz's Navigation Function Based on F...

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8th ieee symposium on large-Scale data analysis and visualization (LDAV)

作者： Han, Hyunwoo Yoon, Taerin Ha, Hyoji Hong, Juwon Lee, Kyungwon Ajou Univ Life Media Interdisciplinary Program Suwon South Korea Ajou Univ Dept Digital Media Suwon South Korea

ISBN: (纸本)9781538668733

For user to analyze large data set with various attributes as desired, rearranging data based on purpose is vital. This study proposes a method to navigate data with a desired purpose of user by improving RadViz visualization through focusing and filtering. To help understand visualization, user studies were conducted using the music data of Spotify. As a result, our system is discovered to be effective at classifying large data set of music with attributes and navigating desired music efficiently.

关键词： Multi-task classification Information visualization RadViz Human-centered computing [visualization toolkits]

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Visualizing results in the SALOME platform for large numerical simulations: an integration of ParaView 4

Visualizing results in the SALOME platform for large numeric...

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ieee symposium on large data analysis and visualization

作者： Ribes, Alejandro Bruneton, Adrien EDF R&D Paris France CEA Paris France

ISBN: (纸本)9781479952151

SALOME is an Open Source numerical simulation platform that allows the complete realization of a numerical study. Indeed, the user can easily plug his core numerical code in the platform, define the problem geometry, mesh it, define the boundary conditions, run the solver on a supercomputer, visualize the result and analyze the data;all these actions are performed in an integrated and coherent environment. SALOME can deal with large numerical simulations, like the ones found in multi-physics and/or parametric studies. In this context, ParaView has been integrated into the platform to benefit from its capacity to visualize large models. In this abstract we give an overview of the capabilities of SALOME/ParaView.

关键词： large simulations visualization numerical simulation ParaView SALOME

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One-Shot Learning for Pose-Guided Person Image Synthesis in the Wild

One-Shot Learning for Pose-Guided Person Image Synthesis in ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Dongqi Fan Tao Chen Mingjie Wang Rui Ma Qiang Tang Zili Yi Qian Wang Liang Chang University of Electronic Science and Technology of China China Mobile Zijin Innovation Institute Zhejiang Sci-Tech University Jilin University University of British Columbia NanJing University China Mobile Research Institute

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Current Pose-Guided Person Image Synthesis (PGPIS) methods depend heavily on large amounts of labeled triplet data to train the generator in a supervised manner. However, they often falter when applied to in-the-wild samples, primarily due to the distribution gap between the training datasets and real-world test samples. While some researchers aim to enhance model generalizability through sophisticated training procedures, advanced architectures, or by creating more diverse datasets, we adopt the test-time fine-tuning paradigm to customize a pre-trained Text2Image (T2I) model. However, naively applying test-time tuning results in inconsistencies in facial identities and appearance attributes. To address this, we introduce a Visual Consistency Module (VCM), which enhances appearance consistency by combining the face, text, and image embedding. Our approach, named OnePoseTrans, requires only a single source image to generate high-quality pose transfer results, offering greater stability than state-of-the-art data-driven methods. For each test case, OnePoseTrans customizes a model in around 48 seconds with an NVIDIA V100 GPU.

关键词： Training visualization Image synthesis Graphics processing units One shot learning Signal processing Stability analysis Generators Speech processing Tuning

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In-situ Processing and Interactive visualization for large-Scaled Numerical Simulations 4

In-situ Processing and Interactive Visualization for Large-S...

引用

ieee symposium on large data analysis and visualization

作者： Chen, Fang Flatken, Markus Hotz, Ingrid Gerndt, Andreas German Aerosp Ctr DLR Simulat & Software Technol Cologne Germany

ISBN: (纸本)9781479952151

With the increasing power of the HPC hardware systems, numerical simulations are heading towards exa-scale computing. Early inspection and analysis of on-going large simulations enables domain experts to obtain first insight into their running simulation process and intermediate results. Compared to conventional post-processing, such in-situ processing has the advantage of keeping data in memory, avoiding to store the large amount of raw data to disk, providing on-the-fly analysis, and preventing early failures in the simulation process. In this poster we present a distributed and scalable software infrastructure, which provides distributed insitu data processing, feature extraction and interactive exploration at user's front-end. We have integrated and extended our system to multiple simulation applications, ranging from Lattice-Boltzmann blood flow simulation to grid based simulation for propulsion systems. A user-interactive front-end is integrated to our system, allowing to directly interact with the visualization of running simulations, gain insight, and make decisions.

关键词： data handling

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Writing, Running, and Analyzing large-scale Scientific Simulations with Jupyter Notebooks 11

Writing, Running, and Analyzing Large-scale Scientific Simul...

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ieee 11th symposium on large data analysis and visualization (LDAV)

作者： Savira, Pambayun Marrinan, Thomas Papka, Michael E. Univ St Thomas St Paul MN 55105 USA Argonne Natl Lab Argonne IL 60439 USA Northern Illinois Univ De Kalb IL 60115 USA

ISBN: (纸本)9781665432832

large-scale scientific simulations typically output massive amounts of data that must be later read in for post-hoc visualization and analysis. With codes simulating complex phenomena at ever-increasing fidelity, writing data to disk during this traditional high-performance computing workflow has become a significant bottleneck. In situ workflows offer a solution to this bottleneck, whereby data is simultaneously produced and analyzed without involving disk storage. In situ analysis can increase efficiency for domain scientists who are exploring a data set or fine-tuning visualization and analysis parameters. Our work seeks to enable researchers to easily create and interactively analyze large-scale simulations through the use of Jupyter Notebooks without requiring application developers to explicitly integrate in situ libraries.

关键词： Computing methodologies Modeling and simulation Simulation types and techniques Interactive simulation visualization visualization application domains Scientific visualization

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ieee symposium on Parallel and large-data visualization and Graphics 2003 (ieee Cat. No.3EX736)

IEEE Symposium on Parallel and Large-Data Visualization and ...

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ieee symposium on Parallel and large-data visualization and Graphics (PVG)

The following topics are dealt with: interative rendering; data visualisation; computational geometry; solid modelling; isosurface extraction; parallel processing; load balancing; workstation cluster; image resolution; distributed memory system; image cache; multiprocessing system; image texture; ray tracing; natural scene; interactive system; feature extraction; hidden feature removal; image retrieval.

关键词： Computer graphics Surface fitting Parallel processing Resource management

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