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

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Learning Semantics for visual Place Recognition Through Multi-scale Attention 21st

Learning Semantics for Visual Place Recognition Through Mult...

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21st International conference on Image analysis and Processing (ICIAP)

作者： Paolicelli, Valerio Tavera, Antonio Masone, Carlo Berton, Gabriele Caputo, Barbara IIT Genoa Italy Politecn Torino Turin Italy CINI Rome Italy

ISBN: (纸本)9783031064302;9783031064296

In this paper we address the task of visual place recognition (VPR), where the goal is to retrieve the correct GPS coordinates of a given query image against a huge geotagged gallery. While recent works have shown that building descriptors incorporating semantic and appearance information is beneficial, current state-of-the-art methods opt for a top down definition of the significant semantic content. Here we present the first VPR algorithm (Code and dataset are available at: https:// ***/valeriopaolicelli/SegVPR) that learns robust global embeddings from both visual appearance and semantic content of the data, with the segmentation process being dynamically guided by the recognition of places through a multi-scale attention module. Experiments on various scenarios validate this new approach and demonstrate its performance against state-of-the-art methods. Finally, we propose the first synthetic-world dataset suited for both place recognition and segmentation tasks.

关键词： visual place recognition Segmentation Attention

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Understanding the Effects of visualizing Missing Values on visual data exploration

Understanding the Effects of Visualizing Missing Values on V...

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IEEE visualization conference (IEEE VIS)

作者： Song, Hayeong Fu, Yu Saket, Bahador Stasko, John Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9781665433358

When performing data analysis, people often confront data sets containing missing values. We conducted an empirical study to understand the effect of visualizing those missing values on participants' decision-making processes while performing a visual data exploration task. More specifically, our study participants purchased a hypothetical portfolio of stocks based on a data set where some stocks had missing values for attributes such as PE ratio, beta, and EPS. The experiment used scatterplots to communicate the stock data. For one group of participants, stocks with missing values simply were not shown, while the second group saw such stocks depicted with estimated values as points with error bars. We measured participants' cognitive load involved in decision-making with data with missing values. Our results indicate that their decision-making workflow was different across two conditions.

关键词： Human-centered computing visualization Empiriacal evaluation Missing data

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The Impact of conflicts on data Sharing for Disaster Risk Reduction 20

The Impact of conflicts on Data Sharing for Disaster Risk Re...

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20th Global Information Systems for Crisis Response and Management conference, ISCRAM 2023

作者： Adrot, Anouck Aguerre, Mercedes DRM UMR CNRS 7088 Université Paris-Dauphine PSL France French Red Cross France

ISBN: (纸本)9798218217495

Cross-border regions are particularly exposed to hazards and require cooperation for Disaster Risk Reduction (DRR). Accordingly, multiple countries have been investing in technology and jointly innovate to share and process data against disasters. However, these countries’ capacity to share data depends on the history and the context of the border itself. Going further, conflicts between countries – may they be past, present or future - can radically question and endanger collaborative efforts to share data for DRR. This collaborative research, involving a cohort of master students and an NGO, explores the influence of conflicts on data sharing and cooperation for DRR. Still in progress, this research examines how conflicts affect data sharing and how DRR actors manage them. It is based on exploratory archive analysis of three distinct cases of cross-border DRR collaboration within the EU borders, as well as experts and actors interviewing. Preliminary findings reveal that conflicts affect DRR at three levels: i) actors, ii) interactions with DRR actors, iii) relations between local DRR actors and institutions. The expected contribution of this research is theoretical, practical and pedagogical. © 2023 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

关键词： Information management

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Pheno-Mapper: An Interactive Toolbox for the visual exploration of Phenomics data 21

Pheno-Mapper: An Interactive Toolbox for the Visual Explorat...

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12th ACM conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB)

作者： Zhou, Youjia Kamruzzaman, Methun Schnable, Patrick Krishnamoorthy, Bala Kalyanaraman, Ananth Wang, Bei Univ Utah Salt Lake City UT 84112 USA Univ Virginia Charlottesville VA USA Iowa State Univ Ames IA USA Washington State Univ Vancouver WA USA

ISBN: (纸本)9781450384506

High-throughput technologies to collect field data have made observations possible at scale in several branches of life sciences. The data collected can range from the molecular level (genotypes) to physiological (phenotypic traits) and environmental observations (e.g., weather, soil conditions). These vast swathes of data, collectively referred to as phenomics data, represent a treasure trove of key scientific knowledge on the dynamics of the underlying biological system. However, extracting information and insights from these complex datasets remains a significant challenge owing to their multidimensionality and lack of prior knowledge about their complex structure. In this paper, we present Pheno-Mapper, an interactive toolbox for the exploratory analysis and visualization of large-scale phenomics data. Our approach uses the mapper framework to perform a topological analysis of the data, and subsequently render visual representations with built-in data analysis and machine learning capabilities. We demonstrate the utility of this new tool on real-world plant (e.g., maize) phenomics datasets. In comparison to existing approaches, the main advantage of Pheno-Mapper is that it provides rich, interactive capabilities in the exploratory analysis of phenomics data, and it integrates visual analytics with data analysis and machine learning in an easily extensible way. In particular, Pheno-Mapper allows the interactive selection of subpopulations guided by a topological summary of the data and applies data mining and machine learning to these selected subpopulations for in-depth exploration.

关键词： phenomics topological data analysis interactive visualization multidimensional biological data

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Sentinel-1 and ALOS data for lineament extraction: a comparative study 13

Sentinel-1 and ALOS data for lineament extraction: a compara...

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conference on Earth Resources and Environmental Remote Sensing/GIS Applications XiiI Part of SPIE Remote Sensing conference

作者： Cardoso-Fernandes, Joana Teodoro, Ana Claudia Lima, Alexandre Menuge, Julian Bronner, Marco Steiner, Ralf Univ Porto Dept Geosci Environm & Spatial Planning Fac Sci Rua Campo Alegre P-4169007 Porto Portugal ICT Inst Earth Sci Porto Pole Portugal Rua Campo Alegre P-4169007 Porto Portugal Univ Coll Dublin Sch Earth Sci & iCRAG Dublin D04 V1W8 Ireland Geol Survey Norway Trondheim Norway Geo Unterweissacher GmbH Hochfilzen Austria

ISBN: (纸本)9781510655409;9781510655393

GREENPEG is a H2020 project developing exploration toolsets for critical materials in pegmatites. Lineament mapping is a powerful tool to identify geological structures at different scales, which is commonly applied in mineral exploration. To extract lineament information, different types of data can be employed, namely: (i) optical remote sensing data, (ii) radar remote sensing data, and (iii) digital elevation models (DEM5). All these data have been used by GREENPEG, where image processing of Sentinel-1 and ALOS (DEM) datasets were evaluated to identify regional-scale tectonic structures, such as faults, that may have controlled pegmatite melt emplacement. Automated geomatics methods to extract lineament information and perform lineament mapping were employed and the mean direction of the extracted lineaments was evaluated through rose diagrams. In general, the results of the radar image processing were affected by noise in the coastal areas and by the topography of the region. ALOS data presented some advantages, due to less influence from topography and human structures (saving time in the visual inspection of the results). Moreover, even though higher thresholds for the minimum length to consider as a lineament were applied to Sentinel-1 images, ALOS-derived lineaments were longer. The main trend of the extracted lineaments is in agreement between the two datasets, although specific trends are clearer in the ALOS-derived lineaments because the shaded reliefs produced already filtered the azimuth of lineaments to be extracted according to light incidence angle. For all three project demonstration sites (Leinster, Ireland;Wolfsberg, Austria;and Tysfjord, Norway) it was possible to identify lineaments that may relate to structures that controlled pegmatite emplacement. This study demonstrates the usefulness of different satellite data in structural mapping and mineral exploration.

关键词： Structural geology mineral exploration satellite geomatics pegmatite critical raw materials GREENPEG

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visual Analytics for Industrial Sensor data analysis 23

Visual Analytics for Industrial Sensor Data Analysis

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23rd International conference on Enterprise Information Systems (ICEIS)

作者： Langer, Tristan Meisen, Tobias Univ Wuppertal Chair Technol & Management Digital Transformat Rainer Gruenter Str 21 D-42119 Wuppertal Germany

ISBN: (纸本)9789897585098

Due to the increasing digitalization of production processes, more and more sensor data is recorded for subsequent analysis in various use cases (e.g. predictive maintenance). The analysis and utilization of this data by process experts raises optimization potential throughout the production process. However, new analysis methods are usually first published as non-standardized Python or R libraries and are therefore not available to process experts with limited programming and data management knowledge. It often takes years before those methods are used in ERP, MES and other production environments and the optimization potential remains idle until then. In this paper, we present a visual analytics approach to facilitate the inclusion of process experts into analysis and utilization of industrial sensor data. Based on two real world exemplary use cases, we define a catalog of requirements and develop a tool that provides dedicated interactive visualizations along methods for exploration, clustering and labeling as well as classification of sensor data. We then evaluate the usefulness of the presented tool in a qualitative user study. The feedback given by the participants indicates that such an approach eases access to data analysis methods but needs to be integrated into a comprehensive data management and analysis process.

关键词： Time Series analysis Industrial Sensor data visual Analytics Analytic Provenance

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The Construction of a visual Quantum Interactive System for Fuzzy Evaluation of Financial Budget Performance based on Big data 6

The Construction of a Visual Quantum Interactive System for ...

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6th International conference on Computing Methodologies and Communication, ICCMC 2022

作者： Wei, Yong Yunnan Grain Industry Group Co. LTD Kunming650000 China

ISBN: (纸本)9781665410281

This paper proposes a new fuzzy evaluation system of financial budget performance based on big data. Based on the characteristics of budget security and efficiency, this paper constructs a four-layer indicator system: target layer, category layer, indicator layer and sub-indicator layer. In the weight analysis and index calculation, a new comprehensive fuzzy evaluation operator including a master-slave multiplication operator and a 0-1 multiplication operator is proposed. Combined with the fuzzy analytic hierarchy process, a multi-operator analytic hierarchy fuzzy evaluation model and corresponding solution method are established. Finally, combined with the visualization of quantum interaction, an exploratory conversation search model based on quantum interference is proposed. In the non-classical correlation judgment theory exploration part, it is pointed out that users have a certain quantum interaction system in the process of correlation judgment. © 2022 IEEE.

关键词： Big data

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LegisLatio: A visualization Tool for Legislative Roll-call Vote data 22

LegisLatio: A visualization Tool for Legislative Roll-call V...

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15th International Symposium on visual Information Communication and Interaction, VINCI2022

作者： Méndez, Gonzalo Gabriel Moreno, Oscar Mendoza, Patricio Escuela Superior Politécnica Del Litoral Guayaquil Ecuador

ISBN: (纸本)9781450398077

Appropriate communication and understanding of political data are key to achieve a healthy dialogue between civil society and political institutions. This is particularly important for data generated by bodies that most directly represent citizens, such as congresses, senates, parliaments, and other forms of legislatures. visualization tools have the potential to support the exploration and understanding of such data and make it more accessible and appealing to the general public. With this vision, we present LegisLatio, an interactive visualization tool that enables open-ended analysis of legislative roll-call vote data from multi-party electoral systems. We describe the design of the tool and illustrate its effectiveness with data generated by the Ecuadorian legislature. We also discuss the findings of a qualitative observation that hints at LegisLatio's potential to promote citizen engagement and participation. © 2022 ACM.

关键词： data visualization

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6th Iberian Robotics conference, Robot 2023

6th Iberian Robotics Conference, Robot 2023

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6th Iberian Robotics conference, Robot 2023

ISBN: (纸本)9783031586750

The proceedings contain 90 papers. The special focus in this conference is on Iberian Robotics. The topics include: Map Merge and Accurate Localization in Multi-robot Systems in Real Environments;category Theory for Autonomous Robots: The Marathon 2 Use Case;Development of a Low-Cost 3D Mapping Technology with 2D LIDAR for Path Planning Based on the A* Algorithm;synPhoRest - A Procedural Generation Tool of Synthetic Photorealistic Forest datasets;Evaluation of Point Cloud data Augmentation for 3D-LiDAR Object Detection in Autonomous Driving;Green Deep Learning: Comparative Study of Road Object Detectors Between Jetson Boards and PC;Exploring Domain Adaptation with Depth-Based 3D Object Detection in CARLA Simulator;improving Energy Performance of Camera Lidar Fusion by Intermittent Human Detection for Social Navigation;visual Tracking of Synthetic Space Platforms in Low Orbit Using International Space Station Video Stream and Rendered Earth Model;driver Activity Recognition by Fusing Multi-object and Key Points Detection;cross-View Generalisation in Action Recognition: Feature Design for Transitioning from Exocentric To Egocentric Views;assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation;A Feasibility Study of a Leader-Follower Multi-robot Formation for TDLAS Assisted Methane Detection in Open Spaces;studying Exploitation and exploration Trade-Off of Cognitive Odour-Guided Search;Performance analysis of ORB-SLAM in Foggy Environments;socially Reactive Navigation Models for Mobile Robots in Dynamic Environments;human Motion Trajectory Prediction Using the Social Force Model for Real-Time and Low Computational Cost Applications;DeepRL-Based Robot Local Motion Planning in Unknown Dynamic Indoor Environments;parallel Curves Path Planning Based on Tangent Segments to Concentric Circles;fuzzy Logic Based Decision-Making for Urban Platooning on Urban Roundabout Scenarios;fast Tunnel Traversal for Ground Vehicles by Bearing Estimation with Neura

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6th Iberian Robotics conference, Robot 2023

6th Iberian Robotics Conference, Robot 2023

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6th Iberian Robotics conference, Robot 2023

ISBN: (纸本)9783031591662

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