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Toward a Dual Attention Model for Image-Text Sentiment Classification

Toward a Dual Attention Model for Image-Text Sentiment Class...

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Artificial Intelligence (AMCAI), IEEE Afro-Mediterranean conference on

作者： Soukaina Fatimi Wafae Sabbar Abdelkrim Bekkhoucha LIM Laboratory Faculty of Sciences and Techniques Mohammedia University Hassan II of Casablanca Mohammedia Morocco

Users are becoming accustomed to uploading text and pictures on social networks to express their feelings or ideas. As a result, multimodal sentiment analysis has drawn more attention as a study area in recent years. Nevertheless, most of the existing multimodal sentiment analysis approaches are focused either on emphasising the sentiment features in textual-visual data or on giving more importance to the correlation between texts and images. Motivated by this observation, we propose a dual attention model for image-text sentiment classification that focuses on both extracting attended visual and textual features relevant to the semantic classification, and uses the selected features to compute the correlation between the visual and textual data. Moreover, we take advantage of both the self-attention mechanism and the cross-modal mechanism to put in place a dual attention model for multimodal sentiment classification. The approach is carefully constructed and extensively explained, offering a strong theoretical base. The current research focuses on presenting a new theoretical method and its overall architecture. However, experimental validation is a crucial next step; a later article will present the experimental findings.

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analysis and visual exploration of prediction algorithms for public bicycle sharing systems 15

Analysis and visual exploration of prediction algorithms for...

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International conference on Computer Graphics, visualization, Computer Vision and Image Processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big data Analytics, data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on Computer Science and Information Systems, MCCSIS 2021

作者： Ordoñez, Alexandra Cortez Vázquez, Pere-Pau ViRVIG Universitat Politècnica de Catalunya Carrer Llorens I Artigas 4-6 Barcelona08028 Spain

ISBN: (纸本)9789898704320

Public bicycle sharing systems have become an increasingly popular means of transportation in many cities around the world. However, the information shown in mobile apps or websites is commonly limited to the system's current status and is of little use for both citizens and responsible planning entities. The vast amount of data produced by these managing systems makes it feasible to elaborate and present predictive models that may help its users in the decision-making process. For example, if a user finds a station empty, the application could provide an estimation of when a new bicycle would be available. In this paper, we explore the suitability of several prediction algorithms applied to this case of bicycle availability, and we present a web-based tool to visually explore their prediction errors under different time frames. Even though a quick quantitative analysis may initially suggest that Random Forest yields a lower error, our visual exploration interface allows us to perform a more thorough analysis and detect subtle but relevant differences between algorithms depending on variables such as the station's behavior, hourly intervals, days, or types of days (weekdays and weekends). This case illustrates the potential of visual representation together with quantitative metrics to compare prediction algorithms with a higher level of detail, which can, in turn, assist application designers and decision-makers to dynamically adjust the best model for their specific scenarios. © 2021 International conference on Computer Graphics, visualization, Computer Vision and Image Processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big data Analytics, data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on Computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Websites

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visual analysis of Intertextuality Based on Knowledge Graph 3

Visual Analysis of Intertextuality Based on Knowledge Graph

引用

3rd International conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Gao, Yi Duan, Chenming Cao, Qiuyang College of Arts & Information Engineering Dalian Polytechnic University Zhuanghe116400 China School of Computer Science and Technology Dalian University of Technology Dalian116024 China City Institute Dalian University of Technology Dalian116102 China

ISBN: (纸本)9781450385046

The rapid growth of the scientific literature is presenting researchers with increasing challenges. That means relying on human resources to complete the mining of massive resources or the exploration of cutting-edge trends in a short period of time is impossible. To address this problem, this paper presents a method for visual literature research based on knowledge graph. The method is to use the software CiteSpace to make a comprehensive visual analysis of the origin, development, themes and frontier trends of intertextuality theory, and use artificial intelligence to process data, information and images, so as to complete the construction of scientific knowledge graph of intertextuality theory, enrich literature resources and improve the scientific research environment. The knowledge graph is a scientific measurement method which can visually present literature research results and ultimately realize the grand goal of artificial intelligence serving the development of scientific research. © 2021 ACM.

关键词： Knowledge graph

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A Monocular Pose Estimation Case Study: The Hayabusa2 Minerva-ii2 Deployment

A Monocular Pose Estimation Case Study: The Hayabusa2 Minerv...

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IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Price, Andrew Yoshida, Kazuya Tohoku Univ Dept Aerosp Engn Sendai Miyagi Japan

ISBN: (纸本)9781665448994

In an environment of increasing orbital debris and remote operation, visual data acquisition methods are becoming a core competency of the next generation of spacecraft. However, deep space missions often generate limited data and noisy images, necessitating complex data analysis methods. Here, a state-of-the-art convolutional neural network (CNN) pose estimation pipeline is applied to the Hayabusa2 Minerva-ii2 rover deployment;a challenging case with noisy images and a symmetric target. To enable training of this CNN, a custom dataset is created. The deployment velocity is estimated as 0.1908 m/s using a projective geometry approach and 0.1934 m/s using a CNN landmark detector approach, as compared to the official JAXA estimation of 0.1924 m/s (relative to the spacecraft). Additionally, the attitude estimation results from the real deployment images are shared and the associated tumble estimation is discussed.

关键词： Space vehicles visualization Pose estimation Pipelines data acquisition Trajectory Convolutional neural networks

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Multi-modal data exploration in a Mixed Reality Environment Using Coordinated Multiple Views

Multi-modal Data Exploration in a Mixed Reality Environment ...

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Human Interface and the Management of Information (HIMI) part of International conference on Human-Computer Interaction (HCii)

作者： Sardana, Disha Kahu, Sampanna Yashwant Gracanin, Denis Matkovic, Kresimir Virginia Tech Blacksburg VA 24061 USA VRVis Res Ctr Vienna Austria

ISBN: (纸本)9783030783204;9783030783211

Immersive analytics is an emerging field of data exploration and analysis in immersive environments. The main idea is to use visual analytics in a fully immersive 3D space. The availability of immersive Extended Reality systems has increased tremendously recently, but it is still not as widely used as conventional 2D displays. We describe an immersive analysis system for spatio-temporal data and compare how it performs in an immersive environment and on a conventional 2D display. We provide a novel view called map-plot that enables analysis and exploration of spatial time series data. We also design an embodied interaction for the map-plot view. The approach is realized based on the coordinated multiple views paradigm. In addition to the map-plot view, several standard views are available. Voice commands and spatial audio are used to support interaction and increase users' embodiment. The findings from a user study show that developed system is much more efficient in a real immersive environment than using conventional 2D displays.

关键词： Immersive analytics Mixed reality Embodied interaction Coordinated multiple views

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Effect of Gaze visualization on Task Efficiency and User Behavior for Guidance Scenarios in Co-Located AR Collaboration

Effect of Gaze Visualization on Task Efficiency and User Beh...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Froso Sarri Katerina Mania School of Electrical & Computer Engineering Technical University of Crete Greece

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Augmented Reality (AR)-enabled collaboration enhances contextual guidance in shared environments, where unambiguous cues are essential, for swift and accurate task completion. Gaze-based cues offer clear, non-verbal indication of intent, reducing interaction ambiguity. While prior research has studied the effectiveness of gaze-based visualization in scenarios where collaborators share the same level of knowledge, less attention has been shown to guidance scenarios, where one user provides task-related information to another. Existing studies often focus on task outcomes (e.g., completion time, error rate) without analyzing gaze data to gain further insight into user behavior and attention. This study leverages gaze-based cues as an active means of communication in guidance scenarios, assessing their impact on both task performance and user behavior through gaze data analysis. The developed system incorporates gaze-based visualizations, including dynamic representations of gaze behavior, to deliver task-critical guidance. These are compared to verbal instructions using quantitative metrics for task effectiveness and gaze analysis, alongside subjective feedback, to determine whether they reduce ambiguity and enhance collaboration. Our study showed that gaze-based visualizations significantly reduced task related errors, with contextual triggered cues offering the best balance between speed and correctness. Gaze analysis revealed that gaze-based visualizations effectively directed participants’ attention to task-relevant areas, reducing unnecessary visual exploration. Participants reported lower perceived workload in gaze-based conditions, further supporting their effectiveness in enhancing collaboration and reducing ambiguity.

关键词： Human computer interaction Measurement Hands visualization Three-dimensional displays Error analysis Collaboration data visualization Information sharing Augmented reality

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NFTeller: Dual Centric visual Analytics of NFT Transactions

NFTeller: Dual Centric Visual Analytics of NFT Transactions

引用

International conference on Big data and Smart Computing (BIGCOMP)

作者： Yifan Cao Xingxing Yang Meng Xia Hongkun Liu Kento Shigyo Wei Zeng Furui Cheng Yang Wang Qianhang Yu Huamin Qu Hong Kong University of Science and Technology Carnegie Mellon University Hong Kong University of Science and Technology (Guangzhou) Hong Kong University of Science and Technology ETH Zürich

Non-fungible tokens (NFTs) can certify the authenticity and scarcity of digital assets on the blockchain. There is an urgent need to identify impact attributes from various potential factors and further evaluate NFT collectibles. Nevertheless, the task is challenging due to the massive amount of heterogeneous and multi-modal data (e.g., social media text, numerical transaction data, and images) in NFT transactions. To this end, we present an interactive visual analytics system, NFTeller, that provides a dual-centric perspective analysis of NFT transactions. The system i) summarizes the temporal evolution and correlation of transaction patterns and dynamic impact attributes of NFT collection projects; ii) presents an augmented chord diagram with a radial stacked bar chart for exploring the co-collected projects and co-occurring whale accounts. We derive in-depth insights from case studies on a real data set to evaluate the systems’ effectiveness and usability.

关键词： Correlation Social networking (online) visual analytics Whales Collaboration Big data Nonfungible tokens

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Fine Characterization of Reefs and Reservoir Distribution of Changxing Formation in Damaoping - Gaofengchang Area, Eastern Sichuan Basin 11th

Fine Characterization of Reefs and Reservoir Distribution of...

引用

11th International Field exploration and Development conference, IFEDC 2021

作者： Zhang, Lin Chen, Li Luo, Ruilan Zhang, Qiang Yu, Hao Yu, Jichen PetroChina Research Institute of Petroleum Exploration and Development Beijing China Chongqing Gas Field Southwest Oil and Gas Company Petro China Chongqing China

ISBN: (纸本)9789811921483

The Damaoping-Gaofengchang area is located at the southeastern end of the Huankaijiang-Liangping Trough in eastern Sichuan, which is controlled by the double tectonic action of northwest and northeast. The Changxing Formation reefs and the Feixianguan Formation shoal facies reservoirs are well developed. Only 4 wells in the main area of Damaoping have good production results, while the other wells have relatively poor production and test results. Based on the existing data of drilling, logging, seismic and development performance, the subdivision of sublayers and the redefinition of reef period are carried out with wavelet transform and sequence stratigraphy. The development model and distribution character of reef are established, combining with seismic forward and inversion characteristics, and reservoir distribution characteristics are evaluated with experimental analysis, development performance, logging interpretation and geological model establishment. The Changxing Formation is divided into 2 sequences and 5 sublayers. The reefs are mainly developed in Sequence ii which has three stages. The first stage develops in the flooded system tract of Sequence ii, and the second and third stages develop in the high-water system tract of Sequence ii. In the seismic profile, the reef is characterized by increased uplift of Changxing top formation, weak amplitude and discontinuous internal weak amplitude of Changxing formation. The three phases of reef are all developed in the main area of Damaoping, which are superposed on the plane to form an unclosed ring feature. It is characterized by three rows of reefs in Damaoping xi area which showed the characteristics of near east-west migration. The reef was formed into a fracture-porous dolomite reservoir through early freshwater dolomization. The fractures improve the seepage capacity of the reservoir, and the production capacity is well. This paper puts forward the method of reef sequence division and fine characterization

关键词： Seismology

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visual analysis of Spatio-temporal Phenomena with 1D Projections

Visual Analysis of Spatio-temporal Phenomena with 1D Project...

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Eurographics / IEEE VGTC conference on visualizaation

作者： Franke, M. Martin, H. Koch, S. Kurzhals, K. Univ Stuttgart Stuttgart Germany Swiss Fed Inst Technol Zurich Switzerland Inst Adv Res Artificial Intelligence Vienna Austria

It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.

关键词： Computer graphics

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An Intelligent visual Big data Analytics Framework for Supporting Interactive exploration and visualization of Big OLAP Cubes 24

An Intelligent Visual Big Data Analytics Framework for Suppo...

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24th International conference Information visualisation (IV)

作者： Ordonez, Carlos Chen, Zhibo Cuzzocrea, Alfredo Garcia-Garcia, Javier Univ Houston Houston TX 77004 USA Haliburton Houston TX USA LORIA Villers Les Nancy France Univ Calabria Commenda Di Rende Italy Univ Nacl Autonoma Mexico C3 Mexico City DF Mexico

ISBN: (纸本)9781728191348

visual big data analytics aims at supporting big data analytics via visual metaphors, with a plethora of applications in modern settings and scenarios. In all these domains, visual big data analytics paradigms offer several advantages, among which some noticeable ones are: (i) fast knowledge understanding from big data sets;(ii) pattern and trend discovery from big data sets;(iii) entity and model discovery from big data sets;(iv) sharing insights among organizations. Among several proposals, OLAP-based visual big data analytics methodologies and tools represents a successful case of visual big data analytics frameworks, which is entirely based on OLAP analysis. In this context, an OLAP cube is typically explored with multiple aggregations selecting different subsets of cube dimensions to analyze trends or to discover unexpected results. Unfortunately, such analytic process is generally manual and fails to statistically explain results. On the basis of these considerations, in this paper we propose an innovative OLAP-shaped visual big data analytics framework that incorporates a state-of-the-art statistical technique for supporting exploration and visualization of OLAP data cubes. An experimental evaluation with a medical data set presents statistically significant results and interactive visualizations, which link risk factors and degree of disease.

关键词： OLAP Cubes visual Big data Analytics Big data analysis Intelligent Big data Systems

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