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

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Toward Improving the Evaluation of visual Attention Models: a Crowdsourcing Approach

Toward Improving the Evaluation of Visual Attention Models: ...

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International Joint conference on Neural Networks (IJCNN) held as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Zanca, Dario Melacci, Stefano Gori, Marco Univ Siena Siena Italy

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169262

Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient locations (spatial distribution of the fixations), when they look in those locations to understand the temporal development of the exploration (temporal order of the fixations), and how they move from one location to another with respect to the dynamics of the scene and the mechanics of the eyes (dynamics). State-of-the-art models focus on learning saliency maps from human data, a process that only takes into account the spatial component of the phenomenon and ignore its temporal and dynamical counterparts. In this work we focus on the evaluation methodology of models of human visual attention. We underline the limits of the current metrics for saliency prediction and scanpath similarity, and we introduce a statistical measure for the evaluation of the dynamics of the simulated eye movements. While deep learning models achieve astonishing performance in saliency prediction, our analysis shows their limitations in capturing the dynamics of the process. We find that unsupervised gravitational models, despite of their simplicity, outperform all competitors. Finally, exploiting a crowd-sourcing platform, we present a study aimed at evaluating how strongly the scanpaths generated with the unsupervised gravitational models appear plausible to naive and expert human observers.

关键词： visual attention models evaluation scanpath fixations saliency crowd-sourcing

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Collaboration Spotting X - A visual Network exploration Tool

Collaboration Spotting X - A Visual Network Exploration Tool

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International conference on Social Networks analysis, Management and Security (SNAMS)

作者： Aleksandar Bobic Jean–Mariele Goff Christian Guetl IPT Department CERN GenevaSwitzerland CoDiS Lab ISDS Graz University of Technology Graz Austria

ISBN: (纸本)9781665494960

Due to many technological advancements, the amount of connected data drastically increased in the last decade. The analysis of this data and the insights it generates show great potential for supporting decision making processes in various industries and aspects of our lives. Multiple visual analytics solutions have been proposed to gain further insights into such data and gain explainable results. However, the majority of existing solutions are either closed sourced, not available or no longer developed. To mitigate the issues above and based on findings from expert interviews conducted using an existing tool, this paper introduces Collaboration Spotting X, a new network-based interactive visual analytics and information retrieval tool prototype. This prototype enables users to explore connected network datasets such as social network data and bibliometric data using multiple visual cues and interactions. Furthermore, to gain an insight into how this prototype is perceived by users and identify further improvements, a preliminary study with a class of 37 computer science graduate students is described. The study findings show that the students perceive Collaboration Spotting X as a useful tool that helps them complete tasks through visualisation and interaction. Additionally, multiple aspects were identified that might have caused users to experience in addition to positive emotions also some negative emotions during usage. These aspects might have also contributed to a lower usability score. Finally, multiple improvement directions have been identified, which will be implemented in future developments.

关键词： Computer science Industries Social networking (online) visual analytics Prototypes Collaboration Security

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Short Paper : Textual vs. visual Fake News: A Deception Showdown

Short Paper : Textual vs. Visual Fake News: A Deception Show...

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IEEE International conference on Cloud Computing in Emerging Markets (CCEM)

作者： Kevin Matthe Caramancion College of Emergency Preparedness Homeland Security and Cybersecurity University at Albany The State University of New York Albany New York United States

This paper explores how the textuality or style of contents (iv) affect the mis/disinformation risk of information consumers. Using a 20-item test that consists of 10 purely textual contents and 10 visual contents, the author tested which could likely to be more deceptive (DV1) to the subjects (N=33). The second part of the analysis measured which among the two ignited more Doubt (DV2) among the participants. The main data analysis technique employed for this study is a paired sample t-test. Important findings of the study include the revelation that purely textual contents can be slightly more deceptive, and visual contents can ignite more Doubt. The intended target audience of this paper are information scientists, digital forensic professionals, communication experts, policymakers possibly seeking references on this aspect.

关键词： visualization Cloud computing data analysis Atmospheric measurements conferences Digital forensics Particle measurements

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VarCopy: a visual Exploratory data analysis Platform for Copy Number Variation Studies

VarCopy: a Visual Exploratory Data Analysis Platform for Cop...

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International conference on Information visualisation (iv)

作者： Fabio Bove Federica Mandreoli Riccardo Martoglia Valentino Pisi Cristian Taccioli Chiara Vischioni FIM - University of Modena and Reggio Emilia Italy MAPS - University of Padova Italy

ISBN: (数字)9781728191348

ISBN: (纸本)9781728191355

The study of such a complex phenomenon as cancer, which depends on several but unexplored and unclear factors, needs new ways to visualize, analyze and combine different data both on species characteristics and genes function. To this respect, we propose a novel platform, named VarCopy, supporting visual Exploratory data analysis (EDA) in the context of Copy Number Variation (CNV) data. The platform will be publicly available as a web application soon, and is, to our best knowledge, the first tool allowing visual, interactive exploration and analysis of the CNV landscape of multiple species, allowing the identification of new target genes that might be useful for biomedical research.

关键词： Knowledge engineering visualization data analysis data visualization Tools data models Cancer

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Efficient visual monitoring of offshore windmill installations with online image annotation and deep learning computer vision

Efficient visual monitoring of offshore windmill installatio...

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Global OCEANS Singapore - U.S. Gulf Coast conference

作者： Langenkaemper, Daniel Moeller, Torben Bruen, Daniel Nattkemper, Tim Wilhelm Bielefeld Univ Biodata Min Grp Bielefeld Germany Saltat GmbH & Ko KG Bielefeld Germany

ISBN: (纸本)9781728154466

The number of offshore windmills keeps growing around the world since they are an essential part of any strategy to produce energy without using nuclear power plants or burning fossil resources. Due to the growing number of installations new monitoring and inspection strategies and routines need to be developed that are not only effective but efficient. In this work we will present first results from a joint project of industry partners and academia that aims at the development of new approaches making use of modern imaging technologies and new methods from artificial intelligence and computer vision research. We investigate three different strategies for collecting digital photos or video and posterior computational analysis using Convolutional Neural Networks (CNN). Our results indicate, that patterns of interest like rust or coating damage can be detected and classified with F-1 scores between 0.80 and 0.94 in photos collected by inspectors. In videos collected with unmanned aerial vehicles (UAV) rust patterns, oils spills and coating damage were detected with F-1 = 0.91. To support users in the time-consuming task of visual data exploration, we present a new visualization method referred to as "virtual twin". Using hand recorded image collections, a data-driven 3D model of a windmill is generated, that can be used to investigate damage patterns in the full context of the windmill and in full detail. Altogether our results indicate, that although each single approach has its limitations, a combination of different imaging methods, deep learning computer vision algorithms and sophisticated visual data exploration by experienced users appears to have potential to overcome the bottleneck in data analysis, interpretation and decision making in the context of the future inspections of offshore windmills, platforms or other constructions.

关键词： Inspection Offshore windmill Offshore wind turbine Unmanned Aerial Vehicles Computer vision Deep Learning Artificial Intelligence

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Drawn threads: Drawing as a visual methodology to enhance qualitative studies

Drawn threads: Drawing as a visual methodology to enhance qu...

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2013 International conference of the Design Research Society Special Interest Group on Experiential Knowledge: Knowing Inside Out -Experiential Knowledge, Expertise and Connoisseurship, EKSIG 2013

作者： Lerpiniere, Claire De Montfort University United Kingdom

ISBN: (纸本)9781907382727

This paper is an analysis of the value that drawing can bring to a formal research methodology. It is based on a series of drawings that were produced to extend and develop a form of qualitative enquiry, an Interpretative Phenomenological analysis (IPA). This analysis was conducted as part of a study of personal textiles that individuals retain and value beyond their practice use, solely for their sentimental or family historical value, termed, the domestic textile archive. Interpretative Phenomenological analysis was used for analysing the individual experience of these textiles, and was found to be a methodologically sound, yet flexible and creative method of uncovering the data. Phenomenological research methods are established as valid means to investigate subjective human experience, across a range of different subject disciplines (Smith, Flowers & Larkin, 2009). Such an interpretative approach was found to be an effective method to discern and illustrate the themes that arise through the individual's engagement with their own archived personal textiles. However, a visual rather than a text-based method is investigated for the supplementary value and illumination such an approach could bring to a qualitative study. In this respect, drawing is explored as a practice-based method of visual inquiry to supplement and support the initial research analysis. Within this model of thinking, drawing is a means of embodied, visual enquiry, which can be used to produce an analytical and evaluative practice that offers further insights to the text-based analysis. Drawing from the final and completed artefacts is a method for making implicit aspects of the experience of their making explicit. The drawn exploration of the material qualities of a textile design enabled an increased understanding of the tacit expertise of the designer or crafts-person, through applied drawing expertise. Copyright © 2013. The copyright rests with the authors and editors.

关键词： Textiles

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2020 1st International conference on Big data Analytics and Practices, IBDAP 2020

2020 1st International Conference on Big Data Analytics and ...

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1st International conference on Big data Analytics and Practices, IBDAP 2020

ISBN: (纸本)9781728181066

The proceedings contain 22 papers. The topics discussed include: research topic modeling: a use case for data analytics on research project data;visual representations of different family structures using an interactive data exploration technique;benefit recommendation system: a use case for pension fund data analytics;BoydCut: bidirectional LSTM-CNN model for Thai sentence segmenter;Sakdas: a python package for data profiling and data quality auditing;digital transformation in business and management research: bibliometric and co-word network analysis;student dropout prediction: a KMUTT case study;and the relations between implementation date of policies and the spreading of COVID-19.

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visual analysis of Biomechanical of lower limbs in 2001–2020 based on VOSviewer

Visual analysis of Biomechanical of lower limbs in 2001–202...

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Health Big data and Smart Sports (HBDSS), International conference on

作者： Xinyi Wei Qian Chen Sijie Yang Ruhao Huang Nanjing Sport Institute Nanjing China SuqianZeda Vocational College Suqian China Hunan Normal University Changsha China

ISBN: (纸本)9781665421898

Taking WOS (web of Science) as the retrieval platform, the retrieval time is from 2001 to 2021. 2180 English core journals on lower limbs biomechanics in recent 20 years are visually included by using “vosviewer 1.6.17”. By analyzing the existing research literature, the number of papers, research countries and key words related to lower limb biomechanics are sorted and summarized hope to understand the current research situation and judge the future research trend, so as to provide reference for further research. VOSviewer is a commonly used visual analysis software, but there are few related analyses on lower limb biomechanics. It is found that in the past two decades, the exploration in related fields has been deepening, among which the United States, Britain and Australia are the active countries with more research in this field, and coordination, speed, model are the most popular words, which reflect the current research trend.

关键词： Biomechanics visualization Biological system modeling Big data Market research Software Australia

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New Analytic Framework of Public Mental Health Prediction Using data Science 1

New Analytic Framework of Public Mental Health Prediction Us...

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International conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)

作者： Marrapu, Hari Krishna Maram, Balajee Reddi, Prasadu GMR Inst Technol Dept IT Rajam Andhra Pradesh India GMR Inst Technol Dept CSE Rajam Andhra Pradesh India Anil Neerukonda Inst Technol & Sci Dept IT Visakhapatnam Andhra Pradesh India

ISBN: (纸本)9781665421119;9781665421126

Nowadays the human-being is suffering from many issues in the society. In the current situation mental health problem is a prevalence issue. Usage of sensor data and dataset is an interesting issue dealing with prediction of mental health of the people living in society. The data science process can be carried out by collecting datasets from various health sector domains and differentiated into three categories such as low, medium, high. This is helpful in detecting weather the person is suffering from any mental issue or not. A sample test is conducted to assess the health conditions of healthy groups and people having mental illness with the help of data mining in data science field. This paper explains about a novel framework for prediction of public mental health condition which are helpful to handle the challenges in the field of data science. Evaluation of data science surveys is different from traditional data analysis due to the scientific approach method used during data classification and filtration. Here the role of "data Science" framework is for promoting the usage of framework by the healthcare professionals to face challenges of mental health.

关键词： data Science Public Health Mental Health Predictive modeling Pervasive computing visual data exploration data Mining

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A comparison of HR2D and 3D seismic anomalies by frequency dependent AVO analysis 4

A comparison of HR2D and 3D seismic anomalies by frequency d...

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4th Applied Shallow Marine Geophysics conference, Held at Near Surface Geoscience 2020

作者： Buckley, F. Tysse, Ø. A/S Norway

ISBN: (纸本)9789462823563

Seismic angle stacks are rarely produced from HR2D seismic site survey datasets. However, angle stacks derived from both a 3D exploration volume and an HR2D site survey dataset have been employed to investigate a shallow section seismic anomaly imaged by both types close to a North Sea well location. Standard site survey methodologies resulted in the interpretation of a shallow gas probability for the anomaly in question and cross-plotting of Intercept/Gradient data confirmed the interpretation of the anomaly as a Class III/iv AVO response. However, frequency decomposed Intercept and Gradient data has revealed subtle differences in the detection of shallow gas by the two datasets. Low frequency velocity dispersion is most apparent on the exploration dataset, whereas the higher frequency HR2D data is more responsive to high frequency attenuation and velocity retardation. The ability of HR2D data to fully image shallow gas accumulations and the general recommendations on maximising the high frequency content of site survey data are questioned. It is proposed that seismic data with a full broadband frequency content is required, in order to image shallow gas in the top-hole section to the fullest extent. © 2020 4th Applied Shallow Marine Geophysics conference, Held at Near Surface Geoscience 2020. All rights reserved.

关键词： Seismology

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