Papers Data Visualization
“Data Visualization” 태그가 달린 논문 335편 · 필터 해제
Interchange Formats for Visualization: LIF and MMIF
Promoting interoperrable computational linguistics (CL) and natural language processing (NLP) application platforms and interchange-able data formats have contributed improving discoverabilty and accessbility of the open…
Data VisualizationInformative Scene Decomposition for Crowd Analysis, Comparison and Simulation Guidance
Crowd simulation is a central topic in several fields including graphics. To achieve high-fidelity simulations, data has been increasingly relied upon for analysis and simulation guidance. However, the information in rea…
Data VisualizationNonlinear Dimensionality Reduction for Data Visualization: An Unsupervised Fuzzy Rule-based Approach
Here, we propose an unsupervised fuzzy rule-based dimensionality reduction method primarily for data visualization. It considers the following important issues relevant to dimensionality reduction-based data visualizatio…
ClusteringData VisualizationDimensionality ReductionContinuous Histogram Loss: Beyond Neural Similarity
Similarity learning has gained a lot of attention from researches in recent years and tons of successful approaches have been recently proposed. However, the majority of the state-of-the-art similarity learning methods c…
Data VisualizationRepresentation LearningDNA Methylation Data to Predict Suicidal and Non-Suicidal Deaths: A Machine Learning Approach
The objective of this study is to predict suicidal and non-suicidal deaths from DNA methylation data using a modern machine learning algorithm. We used support vector machines to classify existing secondary data consisti…
BIG-bench Machine LearningData VisualizationDimensionality ReductionLearning Formation of Physically-Based Face Attributes
Based on a combined data set of 4000 high resolution facial scans, we introduce a non-linear morphable face model, capable of producing multifarious face geometry of pore-level resolution, coupled with material attribute…
Data VisualizationFace ModelSupervised Dimensionality Reduction and Visualization using Centroid-encoder
Visualizing high-dimensional data is an essential task in Data Science and Machine Learning. The Centroid-Encoder (CE) method is similar to the autoencoder but incorporates label information to keep objects of a class cl…
Data VisualizationDimensionality ReductionRetrievalSupervised dimensionality reductionIoT Based Real Time Noise Mapping System for Urban Sound Pollution Study
This paper describes the development of a system that enables real time data visualization via a webapp regarding sound intensity using multiple node devices connected through internet. The prototypes were realized using…
Data VisualizationNCVis: Noise Contrastive Approach for Scalable Visualization
Modern methods for data visualization via dimensionality reduction, such as t-SNE, usually have performance issues that prohibit their application to large amounts of high-dimensional data. In this work, we propose NCVis…
Data VisualizationDimensionality ReductionTwenty Years of Network Science: A Bibliographic and Co-Authorship Network Analysis
Two decades ago three pioneering papers turned the attention to complex networks and initiated a new era of research, establishing an interdisciplinary field called network science. Namely, these highly-cited seminal pap…
Data VisualizationA Markerless Deep Learning-based 6 Degrees of Freedom PoseEstimation for with Mobile Robots using RGB Data
Augmented Reality has been subject to various integration efforts within industries due to its ability to enhance human machine interaction and understanding. Neural networks have achieved remarkable results in areas of …
Data VisualizationObject LocalizationShapeVis: High-dimensional Data Visualization at Scale
We present ShapeVis, a scalable visualization technique for point cloud data inspired from topological data analysis. Our method captures the underlying geometric and topological structure of the data in a compressed gra…
Community DetectionData VisualizationDimensionality ReductionTopological Data Analysis+1A Comparative Study on Crime in Denver City Based on Machine Learning and Data Mining
To ensure the security of the general mass, crime prevention is one of the most higher priorities for any government. An accurate crime prediction model can help the government, law enforcement to prevent violence, detec…
BIG-bench Machine LearningCrime PredictionData VisualizationA Geometric Approach to Archetypal Analysis via Sparse Projections
Archetypal analysis (AA) aims to extract patterns using self-expressive decomposition of data as convex combinations of extremal points (on the convex hull) of the data. This work presents a computationally efficient gre…
Data VisualizationStatistical analysis of Mapper for stochastic and multivariate filters
Reeb spaces, as well as their discretized versions called Mappers, are common descriptors used in Topological Data Analysis, with plenty of applications in various fields of science, such as computational biology and dat…
Data VisualizationTopological Data AnalysisMulti-Modal Neuroimaging Analysis and Visualization Tool (MMVT)
Sophisticated visualization tools are essential for the presentation and exploration of human neuroimaging data. While two-dimensional orthogonal views of neuroimaging data are conventionally used to display activity and…
Data VisualizationEEGElectroencephalogram (EEG)Self Organizing Nebulous Growths for Robust and Incremental Data Visualization
Non-parametric dimensionality reduction techniques, such as t-SNE and UMAP, are proficient in providing visualizations for datasets of fixed sizes. However, they cannot incrementally map and insert new data points into a…
Data VisualizationDimensionality ReductionMixing autoencoder with classifier: conceptual data visualization
In this short paper, a neural network that is able to form a low dimensional topological hidden representation is explained. The neural network can be trained as an autoencoder, a classifier or mix of both, and produces …
Data VisualizationConstructing a Data Visualization Recommender System
Choosing a suitable visualization for data is a difficult task. Current data visualization recommender systems exist to aid in choosing a visualization, yet suffer from issues such as low accessibility and indecisiveness…
Data VisualizationRecommendation SystemsPrecision disease networks (PDN)
This paper presents a method for building patient-based networks that we call Precision disease networks, and its uses for predicting medical outcomes. Our methodology consists of building networks, one for each patient …
Data Visualization