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检索条件"任意字段=19th Data Compression Conference"

共 11663 条记录，以下是11-20 订阅

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Measuring the Performance of VGG-16, VGG-19, and a Concatenated Model Architecture in Toraja Carving Classification 19

Measuring the Performance of VGG-16, VGG-19, and a Concatena...

引用

19th International conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Herman Putra, Muhammad Dani Arya Nasir, Haidawati Darwis, Herdianti St. Hajrah, Mansyur Noor, Megat Nurolazmi M.M. Faculty of Computer Science Universitas Muslim Indonesia Makassar Indonesia MIIT University Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

this study focuses on being able to classify traditional Toraja carvings using Convolutional Neural Networks (CNN), focusing on three CNN architectures, specifically VGG-16, VGG-19, and a model that is concatenated from both. the aim is to determine the most effective architecture and ratio of training data and validation data sharing to achieve the highest classification accuracy. the image dataset consisting of seven different Toraja carving motifs or classes underwent data pre-processing, namely data augmentation, to improve model generalization and reduce overfitting. Experiments were conducted using four scenarios of training data and validation data separation. the final outcome of this research is that VGG-16 reached the best validation performance of 97.36% with a data 90%:10% separation. It manifests its superior ability to Capture the information of complicated Toraja carving motifs. VGG-19 and the combined model also performed well, but the results were still below the best results of VGG-16 and emphasized that the VGG-16 architecture, especially with a data separation of 90%:10%, is the most reliable CNN architecture for accurately classifying Toraja carvings. © 2025 IEEE.

关键词： Convolutional neural networks

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Size Doesn't Matter? Down-Scaling a data Physicalization Does Not Measurably Change Viewers' Mediated Social Interactions 25

Size Doesn't Matter? Down-Scaling a Data Physicalization Doe...

引用

19th International conference on Tangible Embedded and Embodied Interaction

作者： Friedenberger, Tamara Hurtienne, Joern Julius Maximilians Univ Chair Psychol Ergon Wurzburg Germany

ISBN: (纸本)9798400711978

data physicalizations are physical artifacts that represent data across sensory modalities. they are frequently used in informal learning environments, such as museums, which are inherently social spaces. Research on the design choices for data physicalizations and their effects in social contexts is sparse. Previous work examining the size of data physicalizations shows a tendency to favor larger designs to increase artefact-mediated social interactions among viewers (social engagement), but the empirical evidence remains inconclusive. To address this, we empirically investigated the effect of data physicalization size on social engagement and user experience. In this laboratory study, the social engagement between two viewers freely interacting with a data physicalization is analyzed across two sizes. the results do not indicate a clear advantage of a larger design for increasing social engagement. thus, investing additional effort and material resources in making a physicalization larger would compromise sustainability for no measurable change in social engagement.

关键词： data Physicalisation Artifact Scale

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Magnitude Estimation of Multiple data Drifts for Image Classification Neural Network 19

Magnitude Estimation of Multiple Data Drifts for Image Class...

引用

19th International conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Ye, Seongjin Kim, Bumyoon Jeon, Byeungwoo School of Electronic and Electrical Engineering Sungkyunkwan University Suwon Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

data drift, caused by changes in environment from training, can significantly degrade the performance of neural networks in real-world computer vision tasks. Traditional drift detection methods often focus on a single type of drift, limiting their robustness in complex scenarios. In this paper, we extend an existing method that estimates the degree of a single drift for an image classification model by targeting multi-drift problem for which a set of answer keys is prepared for combination of drift levels and the answer keys are used to predict the magnitudes of drift combination applied to the images. We evaluated our extended method using the CIFAR-10 dataset with two drifts of various levels of Gaussian noise and rain effects. Experimental results confirmed that predicting multiple drifts together effectively prevents the overestimation of drift magnitudes. Additionally, the proposed drift detection model further improves accuracy of drift magnitude estimation. © 2025 IEEE.

关键词： data drift Drift detection Drift for Image Model

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data-Driven Decision Management: Multi-Modal Analytics in a Health Case Study 19

Data-Driven Decision Management: Multi-Modal Analytics in a ...

引用

19th International conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Agomuo, Okechukwu Clement Khan, Zohaib Otuomasirichi, Agomuo Ijeoma Uzoma, Agomuo Kingsley Muzamal, Junaid Hussain Department of Operations and Information Systems University of Utah Salt Lake City United States Dept. of Software Engineering FAST NUCES Lahore Pakistan Department of Agricultural Economics University of Nigeria Enugu Nigeria Center for Environmental Management and Green Energy University of Nigeria Enugu Nigeria Fast School of Computing Fast NUCES Lahore Pakistan

ISBN: (纸本)9798331507817

In an era where data is abundant yet underutilized, organizations across various sectors face challenges in extracting actionable insights from complex, multi-modal datasets. To address these challenges, this study proposes a versatile data analytics framework designed to enhance predictive accuracy and support informed decision-making. the framework integrates structured and unstructured data, leveraging advanced Transformer architectures to capture temporal dynamics and complex interactions within the data. In a healthcare use case, the framework demonstrated its effectiveness by achieving an Accuracy of 0.854, an F1-Score of 0.895, and an AUC-ROC of 0.930, significantly outperforming traditional models. By incorporating SHAP for interpretability, the framework ensures that its predictions are both accurate and transparent, making it a valuable tool for decision-makers. While healthcare is one application, the framework’s flexibility allows it to be adapted to a wide range of industries. Future work will focus on validating the framework across different sectors and integrating it into operational workflows to optimize decision-making and outcomes. © 2025 IEEE.

关键词： Electronic health record

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Travel Patterns & conference Intentions: Engaging conference Attendees with Sustainability through Input Physicalization 25

Travel Patterns & Conference Intentions: Engaging Conference...

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19th International conference on Tangible Embedded and Embodied Interaction

作者： Hayes, Sarah Lindrup, Martin Sauve, Kim Heffernan, Denise Bressa, Nathalie von Koingsbruggen, Rosa Zimmerman, Lisa Huron, Samuel Munster Technol Univ Dept Media Commun Cork Ireland Aalborg Univ Dept Comp Sci Human Centered Comp Aalborg Denmark Univ Bath Bath Avon England Munster Technol Univ Nimbus Res Ctr Cork Ireland Inst Polytech Paris LTCI Telecom Paris Palaiseau France Bauhaus Univ Weimar Human Comp Interact Weimar Germany Munster Technol Univ Cork Ireland Inst Polytech Paris Dpt SES CNRS i3 Telecom Paris Palaiseau France

ISBN: (纸本)9798400711978

Against the backdrop of a growing concern with environmental sustainability across HCI research and design, TEI'24 was the first version of the conference to include a sustainability chair. In conjunction with this increasing interest in sustainability, we organised a Studio at TEI'24 to engage the community in a conversation about the sustainability of conferences by using data physicalizations to mediate this discussion. In a one- day Studio, the organisers and attendees constructed two large-scale input physicalizations that were deployed at the conference venue to collect data around conference sustainability from TEI attendees. In this pictorial, we present the outcomes of this Studio, including the two input physicalizations and the collected data. We offer a description of the strategies we employed to design in a more sustainable way, as well as reflections on input physicalizations and the opportunities and challenges they present for facilitating data-driven dialogue.

关键词： Input physicalization conference sustainability participatory data physicalization

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Reflecting on Solo Dining Behavior with Annotated data Physicalization 25

Reflecting on Solo Dining Behavior with Annotated Data Physi...

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19th International conference on Tangible Embedded and Embodied Interaction

作者： Wang, Xiaoyu van Iterson, Hannah Bae, S. Sandra Liang, Rong-Hao Eindhoven Univ Technol Ind Design Eindhoven Netherlands Univ Colorado Boulder ATLAS Inst Boulder CO USA

ISBN: (纸本)9798400711978

Using information and communication technology (ICT) while solo dining can alleviate loneliness but may also lead to unhealthy food choices and decreased satiety. Mindful eating practices are needed to raise awareness about the impact of ICT technology on eating behavior. Our work aims to use technology to augment physical practices and generate physical artifacts by physicalizing sensor data and letting users self-annotate and make sense of the sensor data. With a toolkit that supports constructive physicalization of inertia sensor data related to the users' eating behavior, users increase their awareness of their mundane routine of solo dining with ICT devices by building personalized data physicalization and adding annotations. Results of a five-day preliminary study indicate how annotating data physicalization could be a beneficial intervention for promoting mindful eating behavior in a personal context.

关键词： annotated data physicalization solo-dining quantifying self mindful eating

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Hybrid Voxel Formats for Efficient Ray Tracing 19th

Hybrid Voxel Formats for Efficient Ray Tracing

引用

19th International Symposium on Visual Computing

作者： Arbore, Russel Liu, Jeffrey Wefel, Aidan Gao, Steven Shaffer, Eric Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9783031773914;9783031773921

Voxels are a geometric representation used for rendering volumes, multi-resolution models, and indirect lighting effects. Since the memory consumption of uncompressed voxel volumes scales cubically with resolution, past works have introduced data structures for exploiting spatial sparsity and homogeneity to compress volumes and accelerate ray tracing. However, these works don't systematically evaluate the trade-off between compression and ray intersection performance for a variety of storage formats. We show that a hierarchical combination of voxel formats can achieve Pareto optimal trade-offs between memory consumption and rendering speed. We present a formulation of "hybrid" voxel formats, where each level of a hierarchical format can have a different structure. For evaluation, we implement a metaprogramming system to automatically generate construction and ray intersection code for arbitrary hybrid formats. We also identify transformations on these formats that can improve compression and rendering performance. We evaluate this system with several models and hybrid formats, demonstrating that compared to standalone base formats, hybrid formats achieve a new Pareto frontier in ray intersection performance and storage cost.

关键词： voxels ray tracing compression metaprogramming

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A Proposed Modification of the IxD Process: Sustainable Prototyping Practice for Physical Technology 25

A Proposed Modification of the IxD Process: Sustainable Prot...

引用

19th International conference on Tangible Embedded and Embodied Interaction

作者： Yang, Yanzhuo Elliott, thomas Charles Univ Queensland Brisbane Qld Australia Univ Queensland Sch Elect Engn & Comp Sci St Lucia Qld Australia

ISBN: (纸本)9798400711978

Technology development within HCI is reliant on physical materials for prototyping, especially in the areas of data physicalization and physical computing. Due to the iterative nature of design, prototyping practices often lead to wastage which is contrary to sustainable practice. therefore, we propose an intermediary step in the design process before 'physical' prototyping. A step which leverages virtual technology to allow prototype exploration and rehearsal prior to a physical build. this proposal intends to build upon existing Tangible, Embedded and Embodied Interaction (TEI) calls for HCI sustainability. the authors of this paper are proposing virtual technology as a means of minimising project waste via insertion of a virtual prototype into the current HCI design process.

关键词： Sustainability data Physicalization Physical Computing HCI Design Prototype Virtual Reality Augmented Reality

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Investigation on Training Strategy for Cross-Modal Large Language Models with Speech and Text 19th

Investigation on Training Strategy for Cross-Modal Large Lan...

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19th National conference on Man-Machine Speech Communication

作者： Zheng, Hang Liu, Yuncong Wang, Hankun Yu, Kai Shanghai Jiao Tong Univ Dept Comp Sci & Engn X LANCE Lab Shanghai Peoples R China

ISBN: (纸本)9789819610440;9789819610457

Large language models (LLMs), as exemplified by the GPT series, have demonstrated exceptional performance in NLP tasks. In this work, we attempt to augment these LLMs with speech data training to achieve end-to-end comprehension and generation capabilities for the speech modality, thereby developing models with inherent dual-modal capabilities in both speech and text. To incorporate speech data into language model training, we discretize the speech data and expand the LLM's vocabulary to include these representations. Compared to speech interaction methods that utilize text as an intermediary auxiliary modality, this architecture allows the model to comprehend the abundant paralinguistic information inherent in speech. Based on this, we utilized Llama as the initial model and experimented with various training strategies. We evaluated the resulting models on semantic understanding tasks, such as Blimp and StoryCloze, and compared their performance with current open-source general speech models. the results indicate that the composition of pre-training data has a significant impact on the model's performance.

关键词： Cross-modal LLM Training Mixed Pretraining data

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Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images 19

Evaluating Visuohaptic Integration on Memory Retention of Mo...

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19th ACM SIGGRAPH International conference on Virtual-Reality Continuum and its Applications in Industry, VRCAI 2024

作者： Siqueira Rodrigues, Lucas Nyakatura, John Zachow, Stefan Israel, Johann Habakuk Kosch, thomas HU Berlin Berlin Germany Zuse Institute Berlin Berlin Germany HTW Berlin Berlin Germany

ISBN: (纸本)9798400713484

Scientific visualization and tomographic imaging techniques have created unprecedented possibilities for non-destructive analyses of digital specimens in morphology. However, practitioners encounter difficulties retaining critical information from complex tomographic volumes in their workflows. In light of this challenge, we investigated the effectiveness of visuohaptic integration in enhancing memory retention of morphological data. In a within-subjects user study (N=18), participants completed a delayed match-to-sample task, where we compared error rates and response times across visual and visuohaptic sensory modality conditions. Our results indicate that visuohaptic encoding improves the retention of tomographic images, producing significantly reduced error rates and faster response times than its unimodal visual counterpart. Our findings suggest that integrating haptics into scientific visualization interfaces may support professionals in fields such as morphology, where accurate retention of complex spatial data is essential for efficient analysis and decision-making within virtual environments. © 2024 ACM.

关键词： data assimilation

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