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

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CueCAn: Cue-driven Contextual Attention for Identifying Missing Traffic Signs on Unconstrained Roads

CueCAn: Cue-driven Contextual Attention for Identifying Miss...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Gupta, Varun Subramanian, Anbumani Jawahar, C., V Saluja, Rohit IIT Hyderabad Ctr Visual Informat Technol CVIT Lab Hyderabad India IIT Mandi Mandi India

ISBN: (纸本)9798350323658

Unconstrained Asian roads often involve poor infrastructure, affecting overall road safety. Missing traffic signs are a regular part of such roads. Missing or non-existing object detection has been studied for locating missing curbs and estimating reasonable regions for pedestrians on road scene images. Such methods involve analyzing task-specific single object cues. In this paper, we present the first and most challenging video dataset for missing objects, with multiple types of traffic signs for which the cues are visible without the signs in the scenes. We refer to it as the Missing Traffic Signs Video dataset (MTSVD). MTSVD is challenging compared to the previous works in two aspects i) The traffic signs are generally not present in the vicinity of their cues, ii) The traffic signs' cues are diverse and unique. Also, MTSVD is the first publicly available missing object dataset. To train the models for identifying missing signs, we complement our dataset with 10K traffic sign tracks, with 40% of the traffic signs having cues visible in the scenes. For identifying missing signs, we propose the Cue-driven Contextual Attention units (CueCAn), which we incorporate in our model's encoder. We first train the encoder to classify the presence of traffic sign cues and then train the entire segmentation model end-to-end to localize missing traffic signs. Quantitative and qualitative analysis shows that CueCAn significantly improves the performance of base models.

关键词： Object detection

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Empowering Social Sciences with data visualization - An Insights and explorations into Behavioral Patterns and Urban Dynamics

Empowering Social Sciences with Data Visualization - An Insi...

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Pervasive Computational Technologies (ICPCT), International conference on

作者： Raihana Parveen Yeo Boon Chin K. Naveen B. Sonia B. Ramana G. LakshmiAlekhya Visual Media Science Research Laboratory QIS College of Engineering and Technology Ongole India Faculty of Engineering and Technology Multimedia University

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

visual data is an integral and essential aspect of any science, a powerful tool for description and exploration in social sciences005. Abstract: In this study, we apply new advanced ways of visualization to bring light on steps helping policy makers better understand multifaceted social phenomena using datasets publicly available. Through combining geospatial, temporal and network visualizations, the framework provides an intimate understanding of urban growth patterns of i-Social networks and behavior characteristics. Findings show that attractive visualizations make interpreting and revealing otherwise hidden patterns easier and provide insight into policy. Such an approach would finally close the gap between data complexity and actionable insights, offering social scientists a solid foundation for research with real impact.

关键词： visualization Fluctuations data analysis Correlation Geology Urban planning data visualization Solids Market research Geospatial analysis

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TiVEx: Optimized Processing for Time Series visual exploration

TiVEx: Optimized Processing for Time Series Visual Explorati...

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ACS/IEEE International conference on Computer Systems and Applications

作者： Heba Helal Mohamed A. Sharaf Mohammad M. Masud Panos K. Chrysanthis College of Information Technology United Arab Emirates University UAE School of Computing and Information University of Pittsburgh United States of America

To facilitate fast-visual data analysis, there is a need for recommending top-k views with "interesting" insights automatically. However, working with high-dimensional time series data makes the process of view recommendations difficult. The primary obstacle lies in finding an automatic way to generate views with less processing time (efficiency) while still closely aligning with the ground truth (effectiveness). In this paper, we propose TiVEx (Time Series visual exploration), a technique to address this challenge. TiVEx aims to achieve a balance between efficiency and effectiveness in generating view recommendations. Through extensive experiments, we demonstrate significant cost savings achieved by TiVEx, indicating its efficiency. Furthermore, our analysis delves into the exploration of striking the right balance between efficiency and effectiveness.

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Towards a visual Approach for Representing Analytical Provenance in exploration Processes 25

Towards a Visual Approach for Representing Analytical Proven...

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25th International conference Information visualisation (IV) - AI and visual Analytics and data Science

作者： Menin, Aline Cava, Ricardo Dal Sasso Freitas, Carla Maria Corby, Olivier Winckler, Marco Univ Cote dAzur CNRS INRIA I3S UMR 7271 Sophia Antipolis France Sul Rio Grandense Fed Inst Pelotas RS Brazil Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781665438278

visualization techniques are useful tools to explore data by enabling the discovery of meaningful patterns and causal relationships. The discovery process is often exploratory and requires multiple views to support analyzing different or complementary perspectives to the data. In this context, analytic provenance shows great potential to understand users' reasoning process through the study of their interactions on multiple view systems. In this paper, we present an approach based on the concept of chained views to support the incremental exploration of large, multidimensional datasets. Our goal is to provide visual representation of provenance information to enable users to retrace their analytical actions and to discover alternative exploratory paths without loosing information on previous analyses. We demonstrate that our implementation of the approach, MGExplorer (Multidimensional Graph Explorer), allows users to explore different perspectives to a dataset by modifying the input graph topology, choosing visualization techniques, arranging the visualization space in meaningful ways to the ongoing analysis and retracing their analytical actions. MGExplorer combines multiple visualization techniques and visual querying while representing provenance information as segments connecting views, which each supports selection operations that help define subsets of the current dataset to be explored by a different view. We demonstrate the usage of the tool through a study case where we explore co-authorship data. We assess the approach through performance metrics, temporal ordering of tasks, number of physical actions, and amount of information to be recalled in-between actions applied to the chosen visual exploration scenarios using chained views.

关键词： Analytical provenance Multiple views Chained views Multidimensional data exploration Provenance visualization

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A Comprehensive and Systematic Review of Deep Learning Based Object Recognition Techniques for the visually Impaired 2

A Comprehensive and Systematic Review of Deep Learning Based...

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2nd International conference on Computational Systems and Communication, ICCSC 2023

作者： Kinra, Aakriti Walia, Wamica Sharanya, S. SRM Institute of Science and Technology Kattankulathur Department of Data Science and Business Systems Tamil Nadu Chennai India

ISBN: (纸本)9781665493932

Object detection is one of computer vision's most essential and challenging visual recognition tasks. The primary focus is to detect objects belonging to different classes and assign each one of them a predefined class label. The dearth of support at diagnosis centers, restricted access to actions and data, stigma created by society, and lack of employment frequently lead visually challenged individuals to seclusion. Existing technologies include A Path Force Feedback Belt (PF belt), Eye Substitution, and Radio Frequency Identification Walking Stick (RFIWS). They detect and localize objects to offer the visually impaired an understanding of the environment around them utilizing the operations of sensors. These systems do not provide real-Time responses and are suitable only for outdoor coverage. Due to ultrasonic or radio frequency limitations, the detection range of these systems is between 1m to 5m. The primary intent of this work is to deliver a complete and extensive analysis of the research done in the field of object recognition for VI-challenged people. © 2023 IEEE.

关键词： Object detection

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Overview of the ImageCLEF 2023: Multimedia Retrieval in Medical, Social Media and Internet Applications 14th

Overview of the ImageCLEF 2023: Multimedia Retrieval in Medi...

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14th International conference of the CLEF Association (CLEF)

作者： Ionescu, Bogdan Muller, Henning Dragulinescu, Ana-Maria Yim, Wen-Wai Ben Abacha, Asma Snider, Neal Adams, Griffin Yetisgen, Meliha Rueckert, Johannes de Herrera, Alba Garcia Seco Friedrich, Christoph M. Bloch, Louise Bruengel, Raphael Idrissi-Yaghir, Ahmad Schaefer, Henning Hicks, Steven A. Riegler, Michael A. Thambawita, Vajira Storas, Andrea M. Halvorsen, Pal Papachrysos, Nikolaos Scholer, Johanna Jha, Debesh Andrei, Alexandra-Georgiana Coman, Ioan Kovalev, Vassili Radzhabov, Ahmedkhan Prokopchuk, Yuri Stefan, Liviu-Daniel Constantin, Mihai-Gabriel Dogariu, Mihai Deshayes, Jerome Popescu, Adrian Univ Politehn Bucuresti Bucharest Romania Univ Appl Sci Western Switzerland HES SO Sierre Switzerland Microsoft Redmond WA USA Microsoft Nuance Redmond WA USA Columbia Univ New York NY USA Univ Washington Seattle WA USA Univ Appl Sci & Arts Dortmund Dortmund Germany Univ Essex Colchester Essex England SimulaMet Oslo Norway Sahlgrens Univ Hosp Gothenburg Sweden Northwestern Univ Chicago IL 60611 USA Belarusian State Univ Minsk BELARUS Belarusian Natl Acad Sci Minsk BELARUS CEA LIST Palaiseau France

ISBN: (纸本)9783031424472;9783031424489

This paper presents an overview of the ImageCLEF 2023 lab, which was organized in the frame of the conference and Labs of the Evaluation Forum - CLEF Labs 2023. ImageCLEF is an ongoing evaluation event that started in 2003 and that encourage the evaluation of the technologies for annotation, indexing and retrieval of multimodal data with the goal of providing information access to large collections of data in various usage scenarios and domains. In 2023, the 21st edition of ImageCLEF runs three main tasks: (i) a medical task which included the sequel of the caption analysis task and three new tasks, namely, GANs for medical images, visual Question Answering for colonoscopy images, and medical dialogue summarization;(ii) a sequel of the fusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression);and (iii) a sequel of the social media aware task on potential real-life effects awareness of online image sharing. The benchmark campaign was a real success and received the participation of over 45 groups submitting more than 240 runs.

关键词： Medical text summarization medical image caption analysis visual question answering Generative Adversarial Networks (GANs) late fusion for search diversification and interestingness prediction prediction of effects of online image sharing ImageCLEF lab

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Mondrian Abstraction and Language Model Embeddings for Differential Pathway analysis

Mondrian Abstraction and Language Model Embeddings for Diffe...

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2024 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Abir, Fuad Al Chen, Jake Y. University of Alabama at Birmingham Department of Computer Science BirminghamAL35233 United States School of Medicine BirminghamAL35233 United States

ISBN: (纸本)9798350386226

In this study, we introduce the Mondrian Map, an innovative visualization tool inspired by Piet Mondrian's abstract art, to address the complexities inherent in visualizing biological networks. The Mondrian Map enables clear and meaningful representations of biological pathways by converting intricate biological data into a structured and intuitive format, facilitating a deeper understanding of molecular dynamics. Each pathway is represented by a square whose size corresponds to fold change, with color indicating the direction of regulation (up or down) and statistical significance. The spatial arrangement of pathways is derived from language model embeddings, preserving neighborhood relationships and enabling the identification of clusters of related pathways. Additionally, colored lines highlight potential crosstalk between pathways, with distinctions between short- and long-range functional interactions. In a glioblastoma multiforme (GBM) case study, the Mondrian Map effectively revealed distinct pathway patterns across patient profiles at different stages of disease progression. By surpassing traditional enriched pathway tables and presenting pathways in a relative context without causing visual information overload, this work highlights the tool's potential to enhance downstream bioinformatics analyses by providing a more comprehensive and visually accessible overview of pathway interactions, offering new avenues for therapeutic exploration and personalized medicine. © 2024 IEEE.

关键词： Cell culture

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Beyond visuals : Examining the Experiences of Geoscience Professionals With Vision Disabilities in Accessing data visualizations

Beyond Visuals : Examining the Experiences of Geoscience Pro...

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IEEE visualization conference (VIS)

作者： Cherukuru, Nihanth W. Bailey, David A. Fourment, Tiffany Hatheway, Becca Holland, Marika M. Rehme, Matt Univ Corp Atmospheric Res UCAR Natl Ctr Atmospher Res NCAR Boulder CO 80307 USA

ISBN: (数字)9781665488129

ISBN: (纸本)9781665488129

data visualizations are ubiquitous in all disciplines and have become the primary means of analysing data and communicating insights. However, the predominant reliance on visual encoding of data continues to create accessibility barriers for people who are blind/vision impaired resulting in their under representation in Science, Technology, Engineering and Mathematics (STEM) disciplines. This research study seeks to understand the experiences of professionals who are blind/vision impaired in one such STEM discipline (geo-sciences) in accessing data visualizations. In-depth, semi-structured interviews with seven professionals were conducted to examine the accessibility barriers and areas for improvement to inform accessibility research pertaining to data visualizations through a socio-technical lens. A reflexive thematic analysis revealed the negative impact of visualizations in influencing their career path, lack of data exploration tools for research, barriers in accessing works of peers and mismatched pace of visualization and accessibility research. The article also includes recommendations from the participants to address some of these accessibility barriers.

关键词： Human-centered computing visualization visualization Design and evaluation methods Human-centered computing Accessibility Accessibility technologies

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PCAPFunnel: A Tool for Rapid exploration of Packet Capture Files 25

PCAPFunnel: A Tool for Rapid Exploration of Packet Capture F...

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25th International conference Information visualisation (IV) - AI and visual Analytics and data Science

作者： Uhlar, Juraj Holkovic, Martin Rusnak, Vit Flowmon Networks Brno Czech Republic Brno Univ Technol Fac Informat Technol Brno Czech Republic Masaryk Univ Inst Comp Sci Brno Czech Republic

ISBN: (纸本)9781665438278

Analyzing network traffic is one of the fundamental tasks in both network operations and security incident analysis. Despite the immense efforts in workflow automation, an ample portion of the work still relies on manual data exploration and analytical insights by domain specialists. Current state-of-the-art network analysis tools provide high flexibility at the expense of usability and have a steep learning curve. Recent-often web-based-analytical tools emphasize interactive visualizations and provide simple user interfaces but only limited analytical support. This paper describes the tool that supports the analytical work of network and security operators. We introduce typical user tasks and requirements. We also present the filtering funnel metaphor for exploring packet capture (PCAP) files through visualizations of linked filter steps. We have created PCAPFunnel, a novel tool that improves the user experience and speeds up packet capture data analysis. The tool provides an overview of the communication, intuitive data filtering, and details of individual network nodes and connections between them. The qualitative usability study with nine domain experts confirmed the usability and usefulness of our approach for the initial data exploration in a wide range of tasks and usage scenarios, from educational purposes to exploratory network data analysis.

关键词： data analysis data visualization Network traffic analysis Packet captures

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Public Outlook on E-sports in China: A Content and Sentiment analysis of Social Media 23

Public Outlook on E-sports in China: A Content and Sentiment...

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23rd IEEE International conference on Information Reuse and Integration for data Science (IEEE IRI)

作者： Wang, Yifan Zheng, Xiaochuan Fan, Tianda Wuhan Univ Sch Informat Management Wuhan Peoples R China Wuhan 39 Middle Sch Grade 11 Wuhan Peoples R China

ISBN: (数字)9781665466035

ISBN: (纸本)9781665466035

This paper aims to help people better understand the Chinese public outlook towards e-sports through the calculation and visual analysis of social media big data, so as to provide reference for the development of e-sports industry and relevant decisions. A mixed-method approach is employed to analyze social media texts by combining quantitative sentiment analysis with qualitative topic and keyword analysis. We have completed the topic coding table of public outlook to e-sports and analyzed the topic distribution and trend. We also have carried out keyword extraction and sentiment calculation for each topic to understand their main contents and sentiment changes. The results show that the Chinese public are paying more and more attention to e-sports and they care about E-sports Profession and E-sports Competition most. Especially, discussions on E-sports Culture show a trend of diversified, profound and normalized development. Combined with keyword analysis and sentiment analysis, it's indicated that people are trying to revise their past recognition of e-sports, but it is still closely related to games in the eyes of the public. Besides, people's sentiment towards the e-sports topics has changed from doubt to recognition, and tends to be stable, while they are more willing to exploration on the e-sports education system, e-sports professionalization and the combination between e-sports and traditional sports.

关键词： e-sports social media topic coding keyword analysis sentiment analysis

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