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Multivariate spatial data visualization: a survey

Xiangyang He, Yubo Tao, Qirui Wang, Hai Lin
2019 Journal of Visualization  
The potential features and hidden relationships in multivariate data can assist scientists to gain an in-depth understanding of a scientific process, verify a hypothesis and further discover a new physical  ...  We first introduce the basic concept and characteristics of multivariate spatial data, and describe three main tasks in multivariate data visualization: feature classification, fusion visualization, and  ...  In feature classification, features can be classified based on a scalar value and its derived attributes for univariate data, whereas they are usually defined by multiple variables for multivariate data  ... 
doi:10.1007/s12650-019-00584-3 fatcat:2evmvj76wjhvxe4gfrusvvggpm

Attribute-Based Feature Tracking [chapter]

Freek Reinders, Frits H. Post, Hans J. W. Spoelder
1999 Eurographics  
The task of the visualization system is to extract the features from all frames, to track the features, i.e. to determine the correspondences between features in successive frames, and nally to visualize  ...  The feature data consists of basic attributes such as position, size, and mass. For each set of attributes a number of correspondence functions can be tested which results in a correspondence factor.  ...  This paper describes an attribute-based feature tracking system that solves the correspondence problem based on primary attributes of features, such a s position, size, and mass.  ... 
doi:10.1007/978-3-7091-6803-5_7 fatcat:n6kgo3hdmrdirlrhyb34xn2rsu

Interactive Focus+Context Analysis of Large, Time-Dependent Flow Simulation Data

Helmut Doleisch, Helwig Hauser, Martin Gasser, Robert Kosara
2006 Simulation (San Diego, Calif.)  
Special emphasis is put on new mechanisms to capture time-dependent features, i.e., flow features which are inherently dependent on time.  ...  It supports the flexible specification and visualization of flow features in an interactive setup of multiple linked views.  ...  ACKNOWLEDGEMENTS This work has been carried out as part of the basic research on visualization at the VRVis Research Center in Vienna, Austria (http://www.VRVis.at/vis/), which is partly funded by an Austrian  ... 
doi:10.1177/0037549707078278 fatcat:zyoktnxmcvaqne7bbju2iijn4m

Interactive Vector Field Feature Identification

Joel Daniels, Erik W Anderson, Luis Gustavo Nonato, Cláudio T Silva
2010 IEEE Transactions on Visualization and Computer Graphics  
Feature-based visualizations are generated through a painting interface, performed on this canvas.  ...  Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points.  ...  Each node is split into two based on the median value of a dimension of the node's attribute feature vectors.  ... 
doi:10.1109/tvcg.2010.170 pmid:20975198 fatcat:z6c5jl4kzndj5oy5ipf3rxytke

From one tree to a forest

Qiang Hao, Rui Cai, Yanwei Pang, Lei Zhang
2011 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11  
human effort or rely on strong features that lack of flexibility.  ...  Specifically, we design a set of weak but general features to characterize vertical knowledge (including attribute-specific semantics and inter-attribute layout relationships).  ...  -Learning vertical knowledge learns two kinds of vertical knowledge from a seed site based on its attribute labels and extracted features.  ... 
doi:10.1145/2009916.2010020 dblp:conf/sigir/HaoCPZ11 fatcat:tyvnextnr5apjetl3aqooha5jy

Information Extraction from Visually Rich Documents with Font Style Embeddings [article]

Ismail Oussaid, William Vanhuffel, Pirashanth Ratnamogan, Mhamed Hajaiej, Alexis Mathey, Thomas Gilles
2021 arXiv   pre-print
Our experiments on three real-world complex datasets demonstrate that using token style attributes based embedding instead of a raw visual embedding in LayoutLM model is beneficial.  ...  Information extraction (IE) from documents is an intensive area of research with a large set of industrial applications.  ...  The visual feature of a given token should then be extracted from this feature map.  ... 
arXiv:2111.04045v1 fatcat:i375efp5one6djax4fitvsxbzu

The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform [article]

Jie Li, Haifeng Liu, Chuanghua Gui, Jianyu Chen, Zhenyun Ni, Ning Wang
2019 arXiv   pre-print
We present the design and implementation of a visual search system for real time image retrieval on JD.com, the world's third largest and China's largest e-commerce site.  ...  We demonstrate that our system can support real time visual search with hundreds of billions of product images at sub-second timescales and handle frequent image updates through distributed hierarchical  ...  If it is a new image, the features are extracted and stored in the feature database. The feature database contains each image's high dimensional features and its corresponding product's attributes.  ... 
arXiv:1908.07389v1 fatcat:fx6zrycsufgn3eytrwflk6hj6i

An Effective Image Representation For Visual Information Retrieval

J. You
2015 Zenodo  
The content-based approach is based on the integration of feature-extraction/object-recognition during the management of image databases to overcome the limitation of attribute-based retrieval.  ...  Based on the comprehensive study of the requirements, existing techniques and problems for visual information retrieval, we propose a deductive a g e n t-oriented image database structure and a new wavelet-based  ... 
doi:10.5281/zenodo.37326 fatcat:hslezvczubhknl7agjhcbuicdq

Social Image Analysis From a Non-IID Perspective

Zhe Xu, Ya Zhang, Longbing Cao
2014 IEEE transactions on multimedia  
, called social image attributes, including visual contents, users, tags and timestamps.  ...  By analyzing the relationships among these attributes, we can better understand the semantic activities conducted on such non-IID social images, hence enabling new applications including content organization  ...  As most of the contents are describing local events based on abstract concepts, visual features play a weaker role in the clustering process.  ... 
doi:10.1109/tmm.2014.2342658 fatcat:aqxydotc7jdwdpsjknhjg4prza

NEIL: Extracting Visual Knowledge from Web Data

Xinlei Chen, Abhinav Shrivastava, Abhinav Gupta
2013 2013 IEEE International Conference on Computer Vision  
It is an attempt to develop the world's largest visual structured knowledge base with minimum human labeling effort.  ...  As of 10 th October 2013, NEIL has been continuously running for 2.5 months on 200 core cluster (more than 350K CPU hours) and has an ontology of 1152 object categories, 1034 scene categories and 87 attributes  ...  Researchers have exploited a variety of constraints such as those based on visual similarity [11, 15] , semantic similarity [17] or multiple feature spaces [3] .  ... 
doi:10.1109/iccv.2013.178 dblp:conf/iccv/ChenSG13 fatcat:qks2a3nkanf5vabuqxehikj7ee

Risk prediction in life insurance industry using supervised learning algorithms

Noorhannah Boodhun, Manoj Jayabalan
2018 Complex & Intelligent Systems  
The data dimension has been reduced by feature selection techniques and feature extraction namely, Correlation-Based Feature Selection (CFS) and Principal Components Analysis (PCA).  ...  Machine learning algorithms, namely Multiple Linear Regression, Artificial Neural Network, REPTree and Random Tree classifiers were implemented on the dataset to predict the risk level of applicants.  ...  Comparison between correlation-based feature selection and principal components analysis feature extraction PCA creates new features by combining the existing ones to create better attributes, while correlation  ... 
doi:10.1007/s40747-018-0072-1 fatcat:fmd5bzlxvrguzjwfdvqyq6juy4

Combining Visual Analytics and Content Based Data Retrieval Technology for Efficient Data Analysis

Jose Fernando Rodrigues Jr., Luciana A. S. Romani, Agma Juci Machado Traina, Caetano Traina Jr.
2010 2010 14th International Conference Information Visualisation  
However, visualization techniques often suffer from overlap of graphical items and multiple attributes complexity, making visual selection inefficient.  ...  One of the most useful techniques to help visual data analysis systems is interactive filtering (brushing).  ...  Finally, one can re-examine the visualizations and choose new query centers for further similarity queries, figure 2(d).  ... 
doi:10.1109/iv.2010.101 dblp:conf/iv/RodriguesRTT10 fatcat:q6xpixdffvho7gdyiqrf2nrblq

Survey on Sparse Coded Features for Content Based Face Image Retrieval
English

D. John Victor, G. Selvavinayagam
2014 International Journal of Computer Trends and Technology  
Multiple types of facial features are used to represent discriminality on large scale human facial image database.  ...  Content based image retrieval, a technique which uses visual contents of image to search images from large scale image databases according to users' interests.  ...  Auxiliary visual words are extracted from this visual and textual graph. New retrieval system includes Scale Invariant Feature Transform (SIFT) and Bag-of-words model.  ... 
doi:10.14445/22312803/ijctt-v8p106 fatcat:wgpv2zi2cbaopj5uymbaiazboq

Disentangling Visual Embeddings for Attributes and Objects [article]

Nirat Saini, Khoi Pham, Abhinav Shrivastava
2022 arXiv   pre-print
Extensive experiments show that our method outperforms existing work with significant margin on three datasets: MIT-States, UT-Zappos, and a new benchmark created based on VAW.  ...  Prior works use visual features extracted with a backbone network, pre-trained for object classification and thus do not capture the subtly distinct features associated with attributes.  ...  Similarly, Attribute Affinity Network takes I and I attr , and extracts visual similarity feature v attr for peeled, and dissimilar visual features of I attr , as object feature v ′ obj for orange.  ... 
arXiv:2205.08536v1 fatcat:yutfdkxhgvclvomraegoacqxhu

Semantic, Automatic Image Annotation Based on Multi-Layered Active Contours and Decision Trees

Joanna Isabelle
2013 International Journal of Advanced Computer Science and Applications  
In this paper, we propose a new approach for automatic image annotation (AIA) in order to automatically and efficiently assign linguistic concepts to visual data such as digital images, based on both numeric  ...  Then, visual features are extracted within the regions segmented by these active contours and are mapped into semantic notions.  ...  corresponding metric features from these delineated regions as well as the definition of the semantic attributes based on the visual features (Section II.B), and the (IJACSA) International Journal of Advanced  ... 
doi:10.14569/ijacsa.2013.040828 fatcat:u4aixxypjzdvbby5o4ftvxby64
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