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检索条件"任意字段=Conference on Visual Data Exploration and Analysis IV"

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26th International conference on Neural Information Processing, ICONIP 2019

26th International Conference on Neural Information Processi...

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26th International conference on Neural Information Processing, ICONIP 2019

ISBN: (纸本)9783030368012

The proceedings contain 111 papers. The special focus in this conference is on Neural Information Processing. The topics include: Dense Image Captioning Based on Precise Feature Extraction;improve Image Captioning by Self-attention;dual-Path Recurrent Network for Image Super-Resolution;attention-Based Image Captioning Using DenseNet Features;High-Performance Light Field Reconstruction with Channel-wise and SAI-wise Attention;image Generation Framework for Unbalanced License Plate data Set;cross-Domain Scene Text Detection via Pixel and Image-Level Adaptation;modified Adaptive Implicit Shape Model for Object Detection;an Expert Validation Framework for Improving the Quality of Crowdsourced Clustering;a Label Embedding Method for Multi-label Classification via Exploiting Local Label Correlations;discriminant Feature Learning with Self-attention for Person Re-identification;the Inadequacy of Entropy-Based Ransomware Detection;attention Network for Product Characteristics Prediction Based on Reviews;semi-supervised Regularized Coplanar Discriminant analysis;multi-object Tracking with Conditional Random Field;intra-Modality Feature Interaction Using Self-attention for visual Question Answering;reinforcement Learning with Attention that Works: A Self-Supervised Approach;budget Cost Reduction for Label Collection with Confusability Based exploration;prediction of Refactoring-Prone Classes Using Ensemble Learning;analysis on Dropout Regularization;on a Convergence Property of a Geometrical Algorithm for Statistical Manifolds;SCS: Style and Content Supervision Network for Character Recognition with Unseen Font Style;anomaly Detection Based on the Global-Local Anomaly Score for Trajectory data;patch Selection Denoiser: An Effective Approach Defending Against One-Pixel Attacks;demographic Prediction from Purchase data Based on Knowledge-Aware Embedding;addressing Reward Engineering for Deep Reinforcement Learning on Multi-stage Task;High-Speed Synchronization of Pulse-Coupled

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When David Meets Goliath: Combining Smartwatches with a Large Vertical Display for visual data exploration

When David Meets Goliath: Combining Smartwatches with a Larg...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Horak, Tom Badam, Sriram Karthik Elmqvist, Niklas Dachselt, Raimund Tech Univ Dresden Interact Media Lab Dresden Germany Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9781450356206

We explore the combination of smartwatches and a large interactive display to support visual data analysis. These two extremes of interactive surfaces are increasingly popular, but feature different characteristics-display and input modalities, personal/public use, performance, and portability. In this paper, we first identify possible roles for both devices and the interplay between them through an example scenario. We then propose a conceptual framework to enable analysts to explore data items, track interaction histories, and alter visualization configurations through mechanisms using both devices in combination. We validate an implementation of our framework through a formative evaluation and a user study. The results show that this device combination, compared to just a large display, allows users to develop complex insights more fluidly by leveraging the roles of the two devices. Finally, we report on the interaction patterns and interplay between the devices for visual exploration as observed during our study.

关键词： Cross-device interaction visual analysis data exploration multi-display environment large display smartwatch

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A Synthetic visual analysis System for Time-Varying Network

A Synthetic Visual Analysis System for Time-Varying Network

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IEEE International conference on Computer and Communication Engineering Technology (CCET)

作者： Huang, Jian Zhang, Xiushan Naval Univ Engn Dept Comp Sci Wuhan Hubei Peoples R China

ISBN: (纸本)9781538674376

In recent years, with the rapid development of computer science and information technology, the world is filled and propelled of time-varying and multivariate data. The enormous growth of data in the last decades led to big data challenge in the network security field. Traditional visual analysis method for the time-varying network is inadequate. Efficient methods for visual clutter reduction, network structure exploration and network behavior detection are needed. In this paper, we propose two methods: A triangular based algorithm for time-varying behavior presentation and an improved brush PCP aims to assist the visual analysis task in time-varying network pattern detection. A synthetic visual analysis system is designed and implemented on the basis of these two novel methods. Our system is capable of visually analyzing vast amounts of network data. To better describe and demonstrate the usefulness and performance of our system, we utilize the ChinaVis2015 Challenge dataset as a case study.

关键词： component visual analysis time-varying multivariate data network security threat pattern recognition

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SMARTexplore: Simplifying High-Dimensional data analysis through a Table-Based visual Analytics Approach 13

SMARTexplore: Simplifying High-Dimensional Data Analysis thr...

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13th IEEE conference on visual Analytics Science and Technology (VAST)

作者： Blumenschein, Michael Behrisch, Michael Schmid, Stefanie Butscher, Simon Wahl, Deborah R. Villinger, Karoline Renner, Britta Reiterer, Harald Keim, Daniel A. Univ Konstanz Constance Germany Harvard Univ Cambridge MA 02138 USA

ISBN: (纸本)9781538668610

We present SMARTEXPLORE, a novel visual analytics technique that simplifies the identification and understanding of clusters, correlations, and complex patterns in high-dimensional data. The analysis is integrated into an interactive table-based visualization that maintains a consistent and familiar representation throughout the analysis. The visualization is tightly coupled with pattern matching, subspace analysis, reordering, and layout algorithms. To increase the analyst's trust in the revealed patterns, SMARTEXPLORE automatically selects and computes statistical measures based on dimension and data properties. While existing approaches to analyzing high-dimensional data (e.g., planar projections and Parallel coordinates) have proven effective, they typically have steep learning curves for non-visualization experts. Our evaluation, based on three expert case studies, confirms that non-visualization experts successfully reveal patterns in high-dimensional data when using SMARTEXPLORE.

关键词： High-dimensional data visual exploration pattern-driven analysis tabular visualization subspace aggregation

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visualizing Multidimensional data in Treemaps with Adaptive Glyphs 22

Visualizing Multidimensional Data in Treemaps with Adaptive ...

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22nd International conference Information visualisation (iv) - Biomedical visualization, visualisation on Built and Rural Environments and Geometric Modelling and Imaging

作者： Marques Soares, Anderson Gregorio dos Santos, Diego Hortencio Ramos Barbosa, Cleyton Luiz Goncalves, Aruanda Simoes Resque dos Santos, Carlos Gustavo Meiguins, Bianchi Serique Carvalho Miranda, Elvis Thermo Univ Fed Para Programa Posgrad Ciencia Comp Belem Para Brazil Univ Fed Para Fac Comp Belem Para Brazil

ISBN: (纸本)9781538672020

Treemap is one of the most well-known and used techniques for data analysis in InfoVis. However, it still presents some challenges concerning data representation, such as small items, a large number of hierarchies limiting the visual space, few options for visual data representation (restricted to size, color, label), and others. Thus, this paper presents an InfoVis tool that allows the analysis of multidimensional data using treemaps with glyphs, once they represent more data visually combined visual variables. Besides that, considering treemap scenarios with small area items, an algorithm was developed to analyze which part of the glyph the application should draw since parts of the glyph can still provide useful information. In this way, the glyphs become adaptative to available space. The application has a multilabel decision tree technique that decides which part of the glyph should appear. visualization specialists supplied the training data through a system that showed a diverse range of glyphs' representations. The system varied the glyph's size, the number and the value of the visible visual variables and registered the response of specialists in the training data. Finally, this paper presents images using the treemap with adaptive glyphs approach versos treemap+glyphs and showed that the adaptive approach clears information clutter when treemap items are small.

关键词： Glyphs treemap decision tree

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Notable Site Recognition using Deep Learning on Mobile and Crowd-sourced Imagery

Notable Site Recognition using Deep Learning on Mobile and C...

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International conference on Mobile data Management

作者： Jimin Tan Anastasios Noulas Diego Sáez Rossano Schifanella Center for Data Science New York University New York NY Wikimedia Research Wikimedia Foundation Barcelona Spain ISI Foundation University of Turin Turin Italy

ISBN: (数字)9781728146638

ISBN: (纸本)9781728146645

Being able to automatically recognize notable sites in the physical world using artificial intelligence embedded in mobile devices can pave the way to new forms of urban exploration and open novel channels of interactivity between residents, travellers and cities. Although the development of outdoor recognition systems has been a topic of interest for a while, most works have been limited in geographic coverage due to lack of high quality image data that can be used for training site recognition engines. As a result, prior systems usually lack generality and operate on a limited scope of pre-elected sites. In this work we design a mobile system that can automatically recognise sites of interest and project relevant information to a user that navigates the city. We build a collection of notable sites using Wikipedia and then exploit online services such as Google Images and Flickr to collect large collections of crowd-sourced imagery describing those sites. These images are then used to train minimal deep learning architectures that can be effectively deployed to dedicated applications on mobile devices. By conducting an evaluation and performing a series of online and real-world experiments, we recognise a number of key challenges in deploying site recognition system and highlight the importance of incorporating mobile contextual information to facilitate the visual recognition task. The similarity in the feature maps of objects that undergo identification, the presence of noise in crowd-sourced imagery and arbitrary user induced inputs are among the factors the impede correct classification for deep learning models. We show how curating the training data through the application of a class-specific image de-noising method and the incorporation of information such as user location, orientation and attention patterns can allow for significant improvement in classification accuracy and the election of an end-to-end system that can effectively be used to recognise sites

关键词： Encyclopedias Electronic publishing Internet Task analysis Training Urban areas

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Demonstrating VisTiles: visual data exploration Using Mobile Devices 18

Demonstrating VisTiles: Visual Data Exploration Using Mobile...

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14th International conference on Advanced visual Interfaces (AVI)

作者： Langner, Ricardo Horak, Tom Dachselt, Raimund Tech Univ Dresden Interact Media Lab Dresden Germany

ISBN: (纸本)9781450356169

We demonstrate the prototype of the conceptual VisTiles framework. VisTiles allows exploring multivariate data sets by using multiple coordinated views that are distributed across a set of mobile devices. This setup allows users to benefit from dynamic and user-defined interface arrangements and to easily initiate co-located data exploration sessions. The current web-based prototype runs on commodity devices and is able to determine the spatial device arrangement by either a cross-device pinch gesture or an external tracking system. Multiple data sets are provided that can be explored by different visualizations (e.g., scatterplots, parallel coordinate plots, stream graphs). With this demonstration, we showcase the general concepts of VisTiles and discuss ideas for enhancements as well the potential for application cases beyond data analysis.

关键词： visualization

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ImageCLEF 2019: Multimedia Retrieval in Medicine, Lifelogging, Security and Nature 1

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10th International conference of the CLEF-Association (CLEF)

作者： Ionescu, Bogdan Mueller, Henning Peteri, Renaud Cid, Yashin Dicente Liauchuk, Vitali Kovalev, Vassili Klimuk, Dzmitri Tarasau, Aleh Ben Abacha, Asma Hasan, Sadid A. Datla, Vivek Liu, Joey Demner-Fushman, Dina Duc-Tien Dang-Nguyen Piras, Luca Riegler, Michael Minh-Triet Tran Lux, Mathias Gurrin, Cathal Pelka, Obioma Friedrich, Christoph M. de Herrera, Alba Garcia Seco Garcia, Narciso Kavallieratou, Ergina del Blanco, Carlos Roberto Cuevas, Carlos Vasillopoulos, Nikos Karampidis, Konstantinos Chamberlain, Jon Clark, Adrian Campello, Antonio Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland La Rochelle Univ La Rochelle France Dublin City Univ Dublin Ireland Pluribus One Cagliari Italy Univ Cagliari Cagliari Italy Univ Oslo Oslo Norway Univ Sci Ho Chi Minh City Vietnam Klagenfurt Univ Klagenfurt Austria Inst Informat Minsk BELARUS Philips Res Cambridge Cambridge MA USA Natl Lib Med Bethesda MD USA Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England ETS Ingn Telecomunicac Madrid Spain Univ Aegean Mitilini Greece Univ Bergen Bergen Norway Republican Res & Pract Ctr Pulmonol & TB Minsk BELARUS Filament London England

ISBN: (数字)9783030285777

ISBN: (纸本)9783030285777;9783030285760

This paper presents an overview of the ImageCLEF 2019 lab, organized as part of the conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2019, the 17th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data, (ii) a lifelog task (videos, images and other sources) about daily activities understanding, retrieval and summarization, (iii) a new security task addressing the problems of automatically identifying forged content and retrieve hidden information, and (iv) a new coral task about segmenting and labeling collections of coral images for 3D modeling. The strong participation, with 235 research groups registering, and 63 submitting over 359 runs, shows an important interest in this benchmark campaign.

关键词： Medical retrieval Life logging retrieval and summarization File Forgery Detection Coral image segmentation and classification ImageCLEF benchmarking Annotated data sets

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Analyzing the Effect of Different Partial Overlap Sizes in Perceiving visual Variables

Analyzing the Effect of Different Partial Overlap Sizes in P...

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International conference on Information visualisation (iv)

作者： Diego Hortencio dos Santos Anderson Gregório Marques Soares Rodrigo Santos do Amor Divino Lima Elvis Thermo Carvalho Miranda Carlos Gustavo Resque dos Santos Bianchi Serique Meiguins Programa de P??s-Gradua????o em Ci??ncia da Computa????o Universidade Federal do Par?? Bel??m Brasil Faculdade de Computa????o Universidade Federal do Par?? Bel??m Brasil

Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0%, 50%, 60% and 70%) and number of unique values (3, 4 and 5) to measure the effect they cause on the speed and accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected.

关键词： visualization data visualization Shape Task analysis Image color analysis Tools Layout

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EVALUATION OF VISION-BASED LOCALIZATION AND MAPPING TECHNIQUES IN A SUBSEA METROLOGY SCENARIO

EVALUATION OF VISION-BASED LOCALIZATION AND MAPPING TECHNIQU...

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conference on Underwater 3D Recording and Modelling - A Tool for Modern Applications and CH Recording

作者： Menna, F. Torresani, A. Nocerino, E. Nawaf, M. M. Seinturier, J. Remondino, F. Drap, P. Chemisky, B. COMEX SA Innovat Dept COMEX 36 Bd OceanCS 80143 F-13275 Marseille France Bruno Kessler Fdn FBK 3D Opt Metrol 3DOM Unit Trento Italy Aix Marseille Univ CNRS ENSAM Univ ToulonLIS UMR 7020 Domaine Univ St JeromeBatiment Polytech F-13397 Marseille France Swiss Fed Inst Technol Inst Theoret Phys CH-8093 Zurich Switzerland

Metrology is fundamental in all the applications that require to qualify, verify and validate measured data according to standards or, in other words, to assess their compliance with predefined tolerances. At sea, metrology is commonly associated with the process of measuring underwater structures, mainly pipeline elements widely used in offshore industry. Subsea operations are very expensive;optimizing time and money resources are the core factors driving innovation in the subsea metrology industry. In this study, the authors investigate the use of state-of-art vision-based algorithms, i.e. ORB-SLAM2 and visual Odometry, as a navigation tool to assist and control a Remotely Operated Vehicle (ROV) while performing subsea metrology operations. In particular, the manuscript will focus on methods for assessing the accuracy of both trajectory and tie points provided by the tested approaches and evaluating whether the preliminary real time reconstruction meets the tolerances defined in typical subsea metrology scenarios.

关键词： Underwater photogrammetry SLAM visual odometry subsea metrology ROV deep underwater exploration deformation analysis accuracy evaluation

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