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Efficient Range Distribution Query for Visualizing Scientific Data

https://doi.org/10.1109/pacificvis.2014.60

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Integral histogram: a fast way to extract histograms in Cartesian spaces

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Matching Local Self-Similarities across Images and Videos

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Improving range query estimation on histograms

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Analysis of large-scale scalar data using hixels

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Gaussian mixture model based volume visualization

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Uncertain topology of 3D vector fields

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Transformations for volumetric range distribution queries

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Semi-automatic generation of transfer functions for direct volume rendering

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A universal algorithm for sequential data compression

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Local Histograms for Design of Transfer Functions in Direct Volume Rendering

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On Histograms and Isosurface Statistics

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Distribution-Driven Visualization of Volume Data

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An Information-Theoretic Framework for Flow Visualization

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Relation-Aware Isosurface Extraction in Multifield Data

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An Application of Multivariate Statistical Analysis for Query-Driven Visualization

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TransGraph: Hierarchical Exploration of Transition Relationships in Time-Varying Volumetric Data

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Summed-area tables for texture mapping

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INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Statistical visualization and analysis of large data using a value-based spatial distribution

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Information Guided Data Sampling and Recovery Using Bitmap Indexing

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Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis

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In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations

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A User-Centered Design Study in Scientific Visualization Targeting Domain Experts

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Multivariate Probabilistic Range Queries for Scalable Interactive 3D Visualization

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Efficient Local Histogram Searching via Bitmap Indexing

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Query-Driven Learning for Predictive Analytics of Data Subspace Cardinality

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Statistical Property Guided Feature Extraction for Volume Data

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Efficient and Portable Distribution Modeling for Large-Scale Scientific Data Processing with Data-Parallel Primitives

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