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

共 53955 条记录，以下是191-200 订阅

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SSS-YOLOv8: Track Crack Detection Based on Attention Mechanism and Convolutional Neural Networks

SSS-YOLOv8: Track Crack Detection Based on Attention Mechani...

引用

ieee information Technology and Mechatronics Engineering conference (ITOEC)

作者： Jia Xu Yuqing Song Kaixuan Li School of Automobile and Transportation Tianjin University of Technology and Education China National and Local Joint Engineering Research Center for Intelligent Vehicle Road Collaboration and Safety Technology China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

In practice, detecting track cracks is a challenging problem due to different sizes of cracks and complex backgrounds. In this paper, an improved YOLOv8n model is proposed. First, the SPD-Conv module is introduced into the model, which improves the model's detection accuracy of track cracks, especially fine cracks, by replacing the traditional jump convolution and pooling layers. Then, the Second-order Channel Attention module is introduced, which better utilizes the complex relationship between features and improves the generalization ability of the model in various complex contexts. Finally, the Selective Kernel Attention module is introduced, which adaptively adjusts the size of the receptive field through the input features to better handle features of different scales and further improve the detection performance. The experimental results show that the mean average precision(mAP) of the improved model is 3.4% higher than that of the original model. Therefore, the improved model can be better applied in detecting track cracks in actual detection.

关键词： Adaptation models visualization Target tracking Sensitivity Mechatronics Convolution Feature extraction Convolutional neural networks Kernel information technology

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Map-Free Trajectory Prediction in Traffic with Motion-Pattern-Enhanced Hyper-Relational Interaction Modeling

Map-Free Trajectory Prediction in Traffic with Motion-Patter...

引用

ieee information Technology and Mechatronics Engineering conference (ITOEC)

作者： Zhipeng Zhang School of Software Engineering Huazhong University of Science and Technology Wuhan China National Model Software Institute China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

Trajectory prediction in complex traffic scenes requires both accurate and real-time. Most of the existing advanced map-based Trajectory prediction methods rely heavily on high-definition maps for higher accuracy, but the high-definition maps in open driving environments are extremely expensive to construct and maintain, which hinders the generalization of such models. Another type of map-less methods have a faster reasoning speed, but they perform much lower in complex scenes than the map-based methods due to the lack of map information constraints. To this end, we present a two-stage map-less Trajectory prediction method. First, a contrastive learning-based encoder captures motion patterns, providing implicit constraint semantic. Second, an adaptive multi-granularity hypergraph topology construction module and a bi-directed hypergraph attention module capture complex interaction patterns among agents. Extensive experiments demonstrate that our model achieves state-of-the-art performance when comparing with advanced map-less methods and competitive performance against most map-based methods.

关键词： Adaptation models visualization Accuracy Mechatronics Semantics Neural networks Predictive models Real-time systems Trajectory Topology

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Intelligent Monocular Visual Dynamic Detection Method for Safe Distance of Hot Work Operation

Intelligent Monocular Visual Dynamic Detection Method for Sa...

引用

Power Electronics, Computer Applications (ICPECA), ieee International conference on

作者： Haisheng Li Lei Li Xinjian Lv Ran Zhao Shandong High-speed Construction Management Group Co. Ltd. Jinan China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

The present paper proposes a monocular visual distance detection model, namely DID-CAYOLO, to supervise the irregular operation of workers in construction sites. Visual information is collected using a single CCD sensor, and the YOLOv7 network model is enhanced with CA attention mechanism to improve the accuracy of identifying hot areas, operators, and equipment. Two-dimensional position information of the target is gathered and inverse perspective transformation is performed using a security ranging measurement algorithm to obtain three-dimensional spatial position information and measure distances. Experimental verification demonstrates that the proposed monocular safe distance detection algorithm, DID-CAYOLO, can accurately calculate distances between identified targets. Field tests show an average target detection accuracy of 99.14 % on hot operation datasets with a single image reasoning time of 27.4 ms and ranging accuracy within $\pm 0.11 \ \mathrm{m}$ . This approach fulfills safety distance detection and warning requirements in industrial sites while effectively preventing safety risks associated with hot operations.

关键词： visualization Accuracy Attention mechanisms Target recognition Object detection Position measurement Cameras Distance measurement Real-time systems Calibration

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Duplicated Virtual Co-embodiment Displaying Out-of-view Movements for Tennis Training

Duplicated Virtual Co-embodiment Displaying Out-of-view Move...

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

作者： Kenta Hashiura Amane Yamaguchi Takuji Narumi The University of Tokyo

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Motor skill instruction in virtual environments allows for the presentation of different body information from physical environments, thereby supporting more efficient learning. Virtual Co-embodiment, in which a learner and teacher share control of a single avatar, has demonstrated promising results in motor skill acquisition. However, existing methods are typically limited to movements within the user’s field of view, making their applicability to sports involving out-of-view movements uncertain. To address this issue, we developed a system that displays duplicated avatars in front of the user, allowing the user to observe and adjust their movements more easily. In this study, we focused on tennis return shots and displayed the teacher’s, the learner’s, and the co-embodied avatars, enabling users to recognize and correct differences in their movements through virtual co-embodiment. We conducted a user study on hitting back a tennis ball. We found that providing learners with too much information at once makes correcting their movements difficult. The comments also suggested that reducing the amount of information shown to learners or slowing down their movements may be necessary.

关键词： Training visualization Three-dimensional displays Sports equipment Avatars Virtual environments Switches Motors Synchronization Sports

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Smart Tunnel Traffic Control System using IoT and Machine Learning

Smart Tunnel Traffic Control System using IoT and Machine Le...

引用

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

作者： Subramani, V. Vishnu Kumar, S. Rishikanth, S.R. Poonkuzhali, Ramadoss K S Rangasamy College of Technology Department of Information Technology Tiruchengode India

ISBN: (纸本)9798331521394

Smart Tunnel Traffic Control System Using IoT and Machine Learning' is designed to offer safety and effective management of traffic in single-lane tunnels. The conventional tunnel system does not prohibit big vehicles from entering the tunnel through either end, which may lead to congestion and increase the likelihood of accidents. The designed system uses an ESP32-CAM module to sense the images of the vehicles in real time at any entry point of the tunnel. Using a CNN model, the system classifies incoming vehicles by size, and if a large vehicle is detected, it triggers a red 'STOP' signal and message at the opposite end. In this way, only one large vehicle occupies the tunnel at any time. The system further calculates the transit time in terms of the length of the tunnel and updates it dynamically to handle incoming vehicles. As soon as the tunnel becomes free, a green 'GO' signal allows the next vehicle to move forward. Keywords: loT, ESP32-CAM, CNN, traffic, tunnel safety, automation, image processing, classification, monitoring, accident prevention, congestion, ML. © 2025 ieee.

关键词： Image analysis

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A Transformer-based Multimodal Fusion Model for Efficient Crowd Counting Using Visual and Wireless Signals

A Transformer-based Multimodal Fusion Model for Efficient Cr...

引用

ieee conference on Wireless Communications and Networking

作者： Zhe Cui Yuli Li Le-Nam Tran School of Electrical and Electronic Engineering University College Dublin Ireland College of Electrical Engineering and Automation Shandong University of Science and Technology China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Current crowd-counting models often rely on single-modal inputs, such as visual images or wireless signal data, which can result in significant information loss and suboptimal recognition performance. To address these shortcomings, we propose TransFusion, a novel multimodal fusion-based crowd-counting model that integrates Channel State information (CSI) with image data. By leveraging the powerful capabilities of Transformer networks, TransFusion effectively combines these two distinct data modalities, enabling the capture of comprehen-sive global contextual information that is critical for accurate crowd estimation. However, while transformers are well capable of capturing global features, they potentially fail to identify finer-grained, local details essential for precise crowd counting. To mitigate this, we incorporate Convolutional Neural Networks (CNN s) into the model architecture, enhancing its ability to extract detailed local features that complement the global context provided by the Transformer. Extensive experimental evaluations demonstrate that TransFusion achieves high accuracy with minimal counting errors while maintaining superior efficiency.

关键词： Wireless communication Training visualization Accuracy Computational modeling Transformers Feature extraction Data models Convolutional neural networks Wireless fidelity

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SHAPE: Safe Hydrogen Agile Pipeline Engineering with XR and AI-Enhanced Digital Twins

SHAPE: Safe Hydrogen Agile Pipeline Engineering with XR and ...

引用

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

作者： Nanjia Wang Muskan Sarvesh Bryson Lawton Brody Wells Ryan Kang Hyeongil Nam Sina Rezvani Kangsoo Kim Ron Hugo Simon Park Bob Brennan Frank Maurer University of Calgary

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

The Safe Hydrogen Agile Pipeline Engineering (SHAPE) project aims to develop and study an innovative Digital Twin (DT) system enhanced by eXtended Reality (XR) and Artificial Intelligence (AI) technologies to improve hydrogen pipeline management. This system connects a custom-built pipeline facility with an immersive XR environment, enabling real-time, bidirectional data exchange. By leveraging AI capabilities for leak detection, risk analysis, and anomaly prediction, the system enhances operational safety, efficiency, and reliability. The XR environment offers intuitive navigation, immersive data visualization, and interactive training experiences, supported by intelligent virtual agents and embodied avatars to facilitate collaboration and decision-making. By sharing these developments, we aim to foster discussions with the workshop audience on advancing XR and AI-enabled DT technologies for safer and more sustainable hydrogen pipeline operations.

关键词： Training Shape Pipelines Hydrogen Data visualization Collaboration Safety Digital twins Risk analysis Artificial intelligence

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IoT-Driven Robotic System for Enhanced Nighttime Perimeter Security and Real-Time Surveillance in Smart Environments

IoT-Driven Robotic System for Enhanced Nighttime Perimeter S...

引用

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

作者： Jayachitra, J. Khan, A. Aslam Yuvaraj, V. Tamil Nadu Villupuram India Information Technology Ifet College of Engineering Tamil Nadu Villupuram India

ISBN: (纸本)9798331521394

As a result of the growing demand for automated security, this research study proposes the design and development of a night patrol robot with Raspberry Pi Zero 2 W. The main purpose of the robot is to monitor the areas chosen on its own protecting and checking out safety measures on its own with little or no help from humans. The system comprises of an ultrasonic obstacle detector, an infrared navigational sensor, a monitoring camera and noise harassment detector. Employing AI design, the robot first listens to the sounds happening around and identifies some suspicious actions, and then turns the video on. High-speed data transfer is through Wi-Fi allows real time monitoring and controlling of the robot from a distance. The system's hardware components include an IR sensor, Arduino Uno, Raspberry Pi Zero 2 W, an L298N motor driver, and a specific camera. The paper provides an overview of the system and its design, the implemented algorithms, and some first experimental results of the proposed system, which can be seen as a major further development of the field of autonomous security for both homes and business. © 2025 ieee.

关键词： Remote sensing

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Immersive Analytics for Understanding Ecosystem Services Data

Immersive Analytics for Understanding Ecosystem Services Dat...

引用

ieee Annual International Symposium Virtual Reality

作者： Benjamin Powley Craig Anslow Mairéad De Róiste Stuart Marshall Linnaeus University Victoria University of Wellington

ISBN: (数字)9798331536459

ISBN: (纸本)9798331536466

Planning land use changes requires input from experts across several domains with diverse expertise. Currently available tools were not designed for analysing the required ecosystem services before and after land use changes, or for analysing tradeoffs. Our study is motivated by the need for better tools designed for expert analysts and location knowledgable stakeholders to analyse data relating to land use planning, such as ecosystem services data. The effectiveness of an immersive VR visualization system (Immersive ESS Visualizer) for analysing and visualizing ecosystem services data, is evaluated and compared to existing methods of analysis, paper maps and a 2D screen. Although VR presented some difficulties, the benefits of spatially arranging maps, inspecting fine details, navigation by zooming, and inspection of hillshades provided sufficient advantages to make VR an effective tool for ecosystem services analysis. Participants using Immersive ESS Visualizer arranged handheld maps into 3D layouts, which would not be possible with paper or on the 2D screen. Our research demonstrates that geospatial analysis can be supported by comparative visualization in VR.

关键词： Solid modeling Three-dimensional displays Navigation Stereo image processing Ecosystems Layout Data visualization Virtual reality Inspection Stakeholders

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A Scoping Review and Expert Recommendations for Immersive Solutions towards Predictive Maintenance

A Scoping Review and Expert Recommendations for Immersive So...

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

作者： Renan Guarese Michel Gokan Khan David Lassiter Jérémy Vachier Fabian Johnson Benjamin Edvinsson Anders Bergman Xi Vincent Wang Mario Romero KTH Royal Institute of Technology Sweden EECS CST Digital Futures and KTH AstraZeneca Sweden Linköping University Sweden

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Under an industrial-academic partnership project, the present work aims to map and catalog the different applications of Augmented and Virtual Reality in predictive maintenance (PdM) practices. Through a preliminary scoping review, we targeted two main digital libraries in computing and engineering. Thus, we address the key attributes regarding the types of immersive technologies and the solutions used in several industries for PdM. By categorizing the surveyed prototypes according to 10 parameters in their interaction, visualization, and research methods, we expose the state-of-the-art and valuable knowledge gaps within immersive PdM. After this analysis, we conducted a workshop with 3 manufacturing experts discussing the future of maintenance interfaces, bringing forth their feedback in the shape of recommendations for what to further explore within immersive PdM.

关键词： visualization Three-dimensional displays Reviews Shape conferences Prototypes Mixed reality Virtual reality User interfaces Predictive maintenance

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