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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

共 54083 条记录，以下是451-460 订阅

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Challenges in Enabling Industrial End-Users to use AR and VR for 3D Authoring of Digital Twins for the Factory of the Future

Challenges in Enabling Industrial End-Users to use AR and VR...

引用

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

作者： Clémence Cunin Thierry Duval Cédric Fleury Lab-STICC UMR CNRS 6285 IMT Atlantique Brest

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

In this position paper, we present a brief literature overview about the authoring of digital twins in augmented and virtual reality, with a focus on how they can be used by industrial end-users for three common 3D authoring tasks: mesh segmentation, positioning, and behavior creation. This literature overview shows that most tools are lacking some features that are useful and necessary in this context. These features are (i) being cross-platform, (ii) being easy to use by industrial end-users, and (iii) being able to support asynchronous and synchronous collaboration between several users. Last, we detail shortly how our future work will focus on developing a collaborative authoring tool that will enable several industrial end-users to collaborate in an asymmetric way to achieve the three authoring features identified in the literature overview.

关键词： visualization Authoring systems Three-dimensional displays Collaboration Production facilities Digital twins Workstations Stakeholders Object recognition Testing

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IoT-Driven Predictive Analytics for Precision Harvest Timing with LightGBM Models

IoT-Driven Predictive Analytics for Precision Harvest Timing...

引用

2025 International conference on Visual Analytics and Data visualization, ICVADV 2025

作者： Lourdu Jame, S. Ranganathan, Chitra Sabapathy Saravanan, S.K. Tidke, Bharat Punarselvam, E. Rajmohan, M. Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Kattankulathur Chennai India Mphasis Corporation Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Big Data and Network Security Tamil Nadu Chennai India University Pune India Department of Information Technology Tamil Nadu Namakkal India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331521394

In agriculture, precise harvest time is essential to maximize production and quality. A predictive analytics system powered by the Internet of Things (IoT) and using LightGBM models for accurate harvest time determination is presented in this study. The framework incorporates IoT sensors to gather environmental data, such as soil moisture, light intensity, temperature, and humidity, which are important markers of crop maturity. The data is analyzed using machine learning models, namely LightGBM, to estimate when to harvest accurately. The proposed framework seeks to improve agricultural efficiency by using real-time data analytics. This would allow farmers to make better crop output, waste, and resource utilization choices. Farmers may dynamically adjust their harvesting plans in response to changing crop conditions due to the IoT-driven strategy that enables constant monitoring of environmental variables. By reducing input waste and environmental effects, this capacity enhances agricultural operations' total productivity while supporting sustainable farming practices. The proposed model can transform harvest management using advanced predictive analytics and IoT technologies, as shown by case studies and simulations confirming its efficacy in several agricultural settings. © 2025 ieee.

关键词： Prediction models

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Control of an Underactuated Quadrotor Using LQR and Visual Markers

Control of an Underactuated Quadrotor Using LQR and Visual M...

引用

ieee International conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Gabriel Fernandes Andre G. S. Conceicao Humberto X. De Araújo Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

In this study, a robust Linear Quadratic Regulator (LQR) controller was developed and evaluated for the Bebop 2 quadrotor drone. Polytopic uncertainties in the dynamic model were taken into account in the control design, ensuring robustness. The drone's localization was achieved using fiducial markers and a Kalman Filter for state estimation, integrating visual and positional data. The controller design utilized Linear Matrix Inequalities (LMIs) to optimize performance while accounting for system constraints. A circular trajectory in three-dimensional space was employed to assess the controller's effectiveness in simulation. Results demonstrated precise trajectory tracking, stability, and robust performance despite parameter uncertainties. These findings highlight the applicability of the proposed framework for real-world scenarios involving underactuated UAVs.

关键词： Location awareness visualization Uncertain systems Uncertainty Trajectory tracking Stability analysis Trajectory Vehicle dynamics Quadrotors Drones

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Management of distribution system voltage using solar inverter-a case study of rural feeder

Management of distribution system voltage using solar invert...

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ieee Students' conference on Electrical, Electronics and Computer Science (SCEECS)

作者： Naureen Siddiqui Swapnil Kumar Sahu Priyanka Paliwal Department of Electrical Engineering MANIT Bhopal

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

This paper explores how advanced solar inverters can enhance grid reliability by managing reactive power, a function traditionally handled by mechanical devices like OLTCs and capacitors. As renewable integration grows, dependency on these conventional methods is less practical due to slower response times and maintenance issues. By adjusting inverter power factor (PF) settings, solar inverters can supply both active and reactive power, contributing to voltage stability. This study models a rural feeder with mixed loads and simulates voltage regulation at 11kV and 33kV levels on ETAP software under different loading conditions and tap settings. Results highlight the potential of solar inverters operating at PFs other than unity to reduce voltage drops and enhance system efficiency. Findings emphasize how tailored PF settings, allow solar inverters to stabilize voltage at distribution levels, thus supporting sustainable grid integration)

关键词： Reactive power Electric potential visualization Capacitors Loading Voltage Power system stability Inverters Stability analysis Voltage control

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An Efficient Deep Learning Approach for Food Quality Detection

An Efficient Deep Learning Approach for Food Quality Detecti...

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Industrial Electronics: Developments & Applications (ICIDeA), ieee International conference on-

作者： K Sekar T Yuvarajan J S Tejashwini T Dheepa Department of AIML Rajalakshmi Engineering College Chennai India Department of Computer Science and Engineering Kongunadu College of Engineering and Technology Tiruchirappalli India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

This research aims to develop a deep learning system for assessing food edibility based on user-uploaded photos, addressing the global challenge of food waste. The system leverages the YOLOv8 model, renowned for its efficiency in object detection and classification, to evaluate visual attributes such as color changes, mold, and texture abnormalities, determining whether food is fresh or spoiled. With its advanced detection capabilities, YOLOv8 is well-suited for real-time classification, ensuring quick and accurate identification of spoilage across diverse food types and varying lighting conditions. Unlike traditional systems that often struggle with accuracy, especially when dealing with a wide variety of foods, this approach significantly enhances reliability. By enabling individuals to identify unsafe or spoiled food before consumption, this project contributes to reducing waste and promoting sustainable food practices while improving food safety.

关键词： Food waste visualization Accuracy Transfer learning Lighting Object detection Food safety Real-time systems Reliability Object recognition

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Augmenting Murals: Creating Playful AR Experiences for Wall Art Exhibitions

Augmenting Murals: Creating Playful AR Experiences for Wall ...

引用

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

作者： Axel Bauer Martin Kocur Juergen Hagler UAS Upper Austria Hagenberg Campus

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Outdoor art exhibitions in natural settings offer a popular environment for people to engage with art. With the rapid advancements in augmented reality and mixed reality, immersive technologies and digital augmentations are transforming how people experience art by incorporating animations and interactive elements. However, marker-based augmented reality (AR) approaches, though commonly used, present limitations in large outdoor exhibitions, including labour-intensive setups and restricted exploration freedom for users. To address these challenges, we propose a markerless AR approach utilizing Geospatial tracking, which appears promising for enhancing large-scale outdoor art exhibitions. In this paper, we present the development of a mobile AR application designed to augment murals with dynamic animations and interactive features. We explore various interaction concepts, demonstrating how this technology can be effectively utilized to create innovative, user-centered experiences in outdoor art settings.

关键词： Human computer interaction visualization Art Three-dimensional displays Mixed reality Media Animation Geospatial analysis Indexes Augmented reality

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Multimodal Fake News Prediction using a Two-Transformer Architecture approach with Llama

Multimodal Fake News Prediction using a Two-Transformer Arch...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Vishnutheerth E P Premjith B Sowmya V Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

In today’s era, the spread of fake news is similar to the spread of a forest fire. This is due to the fact that nowadays a vast amount of people use social media. So the probability of misinformation spreading is very high through these online social media handles, and some people even re-post and believe that without even checking the facts. In this project, a multimodal dataset called Weibo is used. The approach includes the creation of image and text embeddings, which are then passed through a two-transformer network, after which the decoder outputs are fused and fed into the Llama model for classification. Data augmentation is employed for the generation of diverse training samples, along with the necessary preprocessing. The results yielded by the model proposed in this research highlights a significant refinement with respect to the traditional ones. Hence, this solution can combat the spread of fake news to some extent.

关键词： Training Adaptation models visualization Accuracy Social networking (online) Blogs Transformers Fake news Context modeling Testing

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Assessing Photorealism of Rendered Objects in Real-World Images: A Transparent and Reproducible User Study

Assessing Photorealism of Rendered Objects in Real-World Ima...

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

作者： Sven Kluge Oliver Staadt Universität Rostock

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

In an era where numerous studies claim to achieve almost photorealism with real-time automated environment capture, there is a need for assessments and reproducibility in this domain. This paper presents a transparent and reproducible user study aimed at evaluating the photorealism of real-world images composed with virtual rendered objects, that have been generated using classical environment capturing and rendering techniques. We adopted a two-alternative forced choice methodology to compare pairs of images created by integrating virtual objects into real photographs, following a classic pipeline. A validation group with defined directional light parameters, derived from previous studies, was included to ensure the study’s accuracy. The findings revealed some insights, suggesting that observers experienced difficulties in differentiating between rendered and real objects. This work establishes the groundwork for future studies, aimed at enhancing the visual fidelity and realism of virtual objects in real-world environments.

关键词： Photorealism visualization Three-dimensional displays Pipelines Virtual reality User interfaces Observers Rendering (computer graphics) Reproducibility of results Real-time systems

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Real-Time Task Detection and Digital Twin Modeling Using Human Posture Estimation in 360-Degree Videos

Real-Time Task Detection and Digital Twin Modeling Using Hum...

引用

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

作者： Hari Iyer Ricardo Eiris Heejin Jeong Arizona State University

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

This paper presents a framework for creating a human-centered digital twin using task detection and human posture estimation (HPE) with Gaussian Splatting from 360-degree videos. Participants performing ladder-related tasks—ascending, working on, and descending a ladder—were recorded using a 360-degree camera. The framework employs HPE to extract key landmark points, and a kinematics-based model detects tasks based on postural transitions observed in the videos. These detected tasks, combined with posture data, enable dynamic visualizations of human movements using Gaussian Splatting. The proposed approach facilitates the creation of a real-time digital twin that visualizes human-environment interactions, capturing the time-series progression of tasks and postures. This method offers scalable real-time monitoring and simulation of human actions, with potential applications in safety training, ergonomics, and human-machine interaction.

关键词： Training Solid modeling Three-dimensional displays Estimation Data visualization Virtual reality Real-time systems Digital twins Safety Videos

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Around the Virtual Campfire: Early UX Insights into AI-Generated Stories in VR

Around the Virtual Campfire: Early UX Insights into AI-Gener...

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ieee International conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Elia Gatti Daniele Giunchi Nels Numan Anthony Steed University College London London UK

ISBN: (数字)9798331521578

ISBN: (纸本)9798331521585

Virtual Reality (VR) presents an immersive platform for storytelling, allowing narratives to unfold in highly engaging, interactive environments. Leveraging AI capabilities and image synthesis offers new possibilities for creating scalable, generative VR content. In this work, we use an LLM-driven VR storytelling platform to explore how AI-generated visuals and narrative elements impact the user experience in VR storytelling. Previously, we presented AIsop, a system to integrate LLM-generated text and images and TTS audio into a storytelling experience, where the narrative unfolds based on user input. In this paper, we present two user studies focusing on how AI-generated visuals influence narrative perception and the overall VR experience. Our findings highlight the positive impact of AI-generated pictorial content on the storytelling experience, highlighting areas for enhancement and further research in interactive narrative design.

关键词： visualization Solid modeling Image synthesis Focusing Virtual reality User experience Artificial intelligence

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