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

共 54092 条记录，以下是401-410 订阅

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Evaluation of LLM-Based VQA Models for Enhancing Battlefield Situation Awareness

Evaluation of LLM-Based VQA Models for Enhancing Battlefield...

引用

International conference on Big Data and Smart Computing (BIGCOMP)

作者： Choulsoo Jang Yoon-Seok Choi Kwang-Yong Kim Jaehwan Kim Sungwoo Jun Changeun Lee Defense & Safety Convergence Reserch Division ETRI Daejeon Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

Multimodal Visual Question Answering (VQA) has emerged as a critical technology for integrating image data and text-based queries to enhance situational awareness in complex environments. By leveraging the capabilities of Large Language Models (LLMs), VQA systems can process external knowledge and provide accurate, context-aware responses. This study explores the development of Korean-supporting multimodal VQA models, focusing on the architectural integration of vision encoders, projection layers, and LLMs. Through pre-training and fine-tuning, the research aims to evaluate these models for tasks requiring language adaptation and external knowledge handling in military scenarios.

关键词： Adaptation models visualization Accuracy Military computing Computational modeling Large language models Refining Computer architecture Data models Question answering (information retrieval)

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AnimateSketches: Animate Sketches with Instance-Aware Mask

AnimateSketches: Animate Sketches with Instance-Aware Mask

引用

International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Haoge Deng Xin Dai Jijin Hu Yonggang Qi Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Sketch animation, the transformation of static sketches into dynamic experiences, is an essential tool for visual expression. Current methods rely on global-level optimization and neglect instance-level priors, resulting in optimization mismatch and overfitting across multiple sketches. To solve this problem, information about the attention map, representing different instances is needed to guide the optimization. In this work, we propose AnimateSketches, a novel optimization-based framework that focuses on animating complex vectorized sketches. We introduce prompt-guided instance-aware mask generation (PGIM), which leverages attention maps from a pretrained diffusion model to guide the optimization of individual sketches. In addition, we use mask-based score distillation sampling (MSDS) to maintain the integrity of untargeted sketches. Quantitative and qualitative evaluations show the superiority of our approach over baseline methods in terms of visual quality and instance-level prompt-guided correspondence.

关键词： visualization Signal processing Animation Diffusion models Acoustics Speech processing Optimization Overfitting

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Self-Convolutional Attention-Based Uncertainty-Aware Network for Single-Image Super-Resolution

Self-Convolutional Attention-Based Uncertainty-Aware Network...

引用

International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jinbin Wang Aiping Yang Zihao Wei Qinghua Hu College of Intelligence and Computing Tianjin University Tianjin China School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Current super-resolution (SR) algorithms rely heavily on annotated data and often ignore the uncertainty in image degradation and features, limiting their real-world application. We propose an uncertainty-aware SR network using a self-convolutional attention mechanism. Our approach focuses on an SR reconstruction network enhanced by a cross-scale self-convolutional attention mechanism within the Transformer framework, which leverages local regions at various resolutions as convolution kernels to enhance high-frequency details. We also design a heteroscedastic uncertainty loss function to learn pixel and feature uncertainties, guiding the network to improve textures and edges adaptively. Extensive experiments show that our method achieves superior visual reconstruction on standard real-world datasets.

关键词： visualization Uncertainty Attention mechanisms Superresolution Signal processing algorithms Transformers Speech processing Image reconstruction Standards Signal resolution

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Boosting Open-Vocabulary Object Detection Performance via Class-Agnostic Pseudo-Labels and MultiModal Hybrid Knowledge

Boosting Open-Vocabulary Object Detection Performance via Cl...

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ziyang Chen Dongqin Liu Jiao Dai Songlin Hu Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Open-vocabulary object detection (OVD) is a significant task identifying objects from categories not included in the training set. Our comprehensive analysis reveals two main issues with existing OVD models: poor generalization of localization network to novel categories and poor quality of class embedding impacting accuracy. We propose two solutions: Localization Network Enhancement based on Class-Agnostic Pseudo-Labels (LNE-CAPL) and Class Embedding Enhancement based on MultiModal Hybrid Knowledge (CEE-MMHK). These methods can be used offline to significantly improve the existing OVD models without affecting their training and inference efficiency. Extensive experiments confirm their effectiveness and universality. Code and models will soon be open-sourced.

关键词： Training Location awareness visualization Accuracy Merging Object detection Speech enhancement Signal processing Boosting Object recognition

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Concept and Considerations for the Development of an information Database for Efficient International Freight Transport

Concept and Considerations for the Development of an Informa...

引用

International conference on Computational Cybernetics (ICCC)

作者： Petra Opitz Tamás Haidegger Enikö Nagy John von Neumann Faculty of Informatics Óbuda University Budapest Hungary University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary School of Computing Queen's University Kingston ON John von Neumann Faculty of Informatics Óbuda University Antal Bejczy Center for Intelligent Robotics Budapest Hungary

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

International freight transport is a growing market and a crucial component of the global economy, enabling the seamless flow of goods across regions and supporting global trade. However, the industry faces significant challenges, particularly in road transport orchestration, due to the increasing complexity of operations and the demand for real-time decision-making. This study sketched the algorithmic and programming framework to address these challenges by presenting an optimized database architecture designed to improve decision support systems for freight transport. The proposed system architecture may leverage the flexibility and scalability of NoSQL databases to manage large, semi-structured datasets in the future, while REST APIs enable seamless integration and real-time data manipulation. To enhance usability and transparency, the system incorporates advanced data visualization tools, allowing stakeholders to derive actionable insights and improve operational efficiency. By focusing on areas such as real-time tracking, sustainability, and process optimization, this work not only addresses current operational needs but also provides a robust foundation for future developments, including advanced analytics and mobile application integration. This contribution supports the logistics industry's shift toward more adaptive, efficient, and sustainable transport solutions.

关键词： Industries NoSQL databases Data visualization Systems architecture Real-time systems Visual databases Usability Sustainable development Optimization Logistics

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Investigating Human Factors in Mako-Assisted Total Knee Arthroplasty Surgeries 25

Investigating Human Factors in Mako-Assisted Total Knee Arth...

引用

ACM/ieee International conference on Human-Robot Interaction (HRI)

作者： Jasper Vermeulen Alan Burden Glenda Caldwell Müge Belek Fialho Teixeira Matthias Guertler Faculty of Engineering Queensland University of Technology Brisbane Australia Faculty of Engineering University Sydney Technology Sydney Australia

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

This paper presents a preliminary investigation of the human factors underpinning successful Human-Robot Collaboration (HRC) in Mako-assisted Total Knee Arthroplasty (TKA) surgeries. This investigation is critical because most prior studies on human factors in Robot-Assisted Surgeries (RAS) have focused on the da Vinci surgical robot, a teleoperated robot. It could be valuable to identify what human factors might enhance or restrict HRC in Mako-assisted surgeries. We analyzed six surgical videos demonstrating how the Mako is utilized in TKA surgeries. We performed visual and thematic analyses. The findings indicate that the Mako system improves communication through the different screens in the operation theatre. These screens promote collaboration by visually sharing relevant information with all team members. Mako-assisted surgeries also introduce several challenges related to workflow disruptions. Future work aims to compare the insights of this study with other types of Mako-assisted surgeries.

关键词： Employee welfare visualization Medical robotics Surgery Human-robot interaction Focusing Collaboration Human factors Knee replacement Videos

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From Boxes to Blueprints: An Investigation of User Expectations and Design Strategies for Spatial Augmented Reality UX/UI

From Boxes to Blueprints: An Investigation of User Expectati...

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

作者： Ha Chau Nguyen Andrew Cunningham Peter Schumacher James A. Walsh Australian Research Centre for Interactive and Virtual Environments University of South Australia Adelaide Australia

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Designing complex buildings requires certain precisions to assess real-world feasibility and align stakeholders' expectations. Existing design tools often fail to convey scale and physical presence and are limited by perceived inaccuracies, low visual fidelity, and high costs. This research combines cardboard boxes with current Spatial Augmented Reality (SAR) setups for rapid prototyping, where boxes serve as life-size, physical representations that can be overlaid with digital information to enable real-time design modifications. A thematic study was conducted with fifteen participants involved tasks such as arranging physical boxes to prototype a kitchen layout, labelling the boxes, and conceptualizing SAR interfaces and experiences without considering SAR's technical limitations. Key findings highlight touch-based interfaces and gesture controls, especially with visual cues, as the preferred input methods, optimal projection locations on the front and top of boxes and walls, and carousel-style user interfaces as the most favored design. Further insights contribute toward the development of a comprehensive framework for ubiquitous spatial computing.

关键词： visualization Technological innovation Three-dimensional displays Spatial augmented reality Layout Buildings Virtual reality Real-time systems Spatial computing Stakeholders

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Novel Approach for Early-Stage Ovarian Cancer Prediction and Reducing Recurrence: A Comprehensive Review

Novel Approach for Early-Stage Ovarian Cancer Prediction and...

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

作者： Daruvuri, Rajesh Puli, Balaram Sundaramoorthy, Pandian Vamsilala, Purushothapatnapu Naga Venkata Jebaranjani, B. Sathya, R. University of Cumberlands AtlantaGA United States Everest Computers Inc Department of Engineering and Data Science RoswellGA30076 United States El CIC-1W-AMI Ibm Sandy SpringsGA30328 United States Vignan's Lara Institute of Technology and Science Guntur district Andhra Pradesh 522213 India Vsb College of Engineering Technical Campus Coimbatore India Kongunadu College of Engineering and Technology Department of Information Technology Trichy India

ISBN: (纸本)9798331521394

Ovarian cancer is one of the most difficult cancers to diagnose at an early stage because its symptoms are subtle. Accurate classification of histological subtypes of ovarian cancer is crucial for effective treatment planning and improving survival rates. This project employs advanced deep learning methods, namely Convolutional Neural Networks (CNNs), to analyze and classify ovarian cancer subtypes based on medical imaging data. The system makes use of pre-processing techniques, such as resizing, normalization, and augmentation, to improve the quality and diversity of training data. A custom-trained CNN model is used to classify subtypes such as high-grade serous carcinoma, low-Grade Serous, endometrioid, mucinous Carcinoma, clear cell carcinoma, among others. In the final application, an intuitive interface is created for clinicians to upload images with real-time subtype predictions, supporting quicker and more informed decisions. The proposed survey points to the potential of AI-driven tools in advancing cancer diagnostics. © 2025 ieee.

关键词： Convolutional neural networks

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Enhancing Customer Experience in Retail for Adaptive Store Layouts with Reinforcement Learning

Enhancing Customer Experience in Retail for Adaptive Store L...

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Visual Analytics and Data visualization (ICVADV), International conference on

作者： P. Suresh T Sivakumar N. Revathy M. Pandi Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of Master of Computer Applications Hindustan College of Arts and Science Coimbatore Tamil Nadu India Department of Information Technology SRM Madurai College for Engineering and Technology Sivagangai Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

In the competitive retail industry, improving customer experience is essential for increasing sales and cultivating brand loyalty. A crucial determinant of consumer happiness is the shop layout, which impacts customers' navigation, exploration, and interaction with merchandise. Traditional store layouts are often inflexible and do not adjust to evolving customer behaviour, hence diminishing their efficacy in enhancing the shopping experience. This paper examines the use of Reinforcement Learning (RL) to create adaptable shop layouts that adjust based on real-time consumer interactions. Through the analysis of customer behaviour and feedback, RL algorithms may dynamically modify the layout of merchandise, aisles, and promotional areas, therefore optimizing the retail environment for both consumers and merchants. The RL algorithm analyses historical data, progressively optimizing store layouts to correspond with consumer preferences, so improving the entire shopping experience. It provides substantial advantages, such as enhanced consumer involvement, more operational efficiency, and elevated revenue designs. It examines the potential of RL in revolutionizing retail settings in optimizing adaptable shop layouts and its effects on consumer happiness and corporate performance.

关键词： Technological innovation ieee merchandise Heuristic algorithms Visual analytics Layout Reinforcement learning Real-time systems Internet of Things Artificial intelligence Optimization

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Haptic Augmentation by a Wrist Mounted Device with Laser Speckle Vibration Sensing and Hand Projection

Haptic Augmentation by a Wrist Mounted Device with Laser Spe...

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

作者： Shun Hanai Yuto Takeuchi Yushi Sato Yoshihiro Okamoto Daisuke Iwai Kosuke Sato Osaka University

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

We propose the wrist-mounted human augmentation device with laser speckle vibration sensing and hand projection that intuitively presents the vibration characteristics of distant objects to the user. By improving the portability limitations of conventional stationary systems, our wearable device can be used while moving or performing tasks. The system consists of a laser speckle vibration sensing unit using a high-speed event camera and a projection-based extended hand via a video projector. It suppresses body sway noise through threshold processing while providing tactile feedback to the user. Additionally, the visual representation of the extended hand allows users to recognize the source of the tactile stimuli intuitively. The proposed system holds potential for various applications, such as remote object inspection.

关键词： Hands Vibrations Wrist visualization Measurement by laser beam Laser feedback Speckle Sensors Laser applications Wearable devices

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