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检索条件"任意字段=International Conference on Computer Graphics, Imaging and Visualization"

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Investigating the Apple Vision Pro Spatial Computing Platform for GPU-Based Volume visualization

Investigating the Apple Vision Pro Spatial Computing Platfor...

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international conference on Visualisation, VIS

作者： Camilla Hrycak David Lewakis Jens Krüger University of Duisburg-Essen

ISBN: (数字)9798350354850

ISBN: (纸本)9798350354867

In this paper, we analyze the Apple Vision Pro hardware and the visionOS software platform, assessing their capabilities for volume rendering of structured grids—a prevalent technique across various applications. The Apple Vision Pro supports multiple display modes, from classical augmented reality (AR) using video see-through technology to immersive virtual reality (VR) environments that exclusively render virtual objects. These modes utilize different APIs and exhibit distinct capabilities. Our focus is on direct volume rendering, selected for its implementation challenges due to the native graphics APIs being predominantly oriented towards surface shading. Volume rendering is particularly vital in fields where AR and VR visualizations offer substantial benefits, such as in medicine and manufacturing. Despite its initial high cost, we anticipate that the Vision Pro will become more accessible and affordable over time, following Apple’s track record of market expansion. As these devices become more prevalent, understanding how to effectively program and utilize them becomes increasingly important, offering significant opportunities for innovation and practical applications in various sectors.

关键词： visualization Technological innovation Visual analytics Superresolution graphics processing units Rendering (computer graphics) Hardware Workstations Spatial computing Engines

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In-Situ Techniques on GPU-Accelerated Data-Intensive Applications 19

In-Situ Techniques on GPU-Accelerated Data-Intensive Applica...

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19th IEEE international conference on e-Science, e-Science 2023

作者： Ju, Yi Li, Mingshuai Perez, Adalberto Bellentani, Laura Jansson, Niclas Markidis, Stefano Schlatter, Philipp Laure, Erwin Max Planck Computing and Data Facility Germany Kth Royal Institute of Technology Sweden Cineca Italy Technical University of Munich Germany Friedrich-Alexander-Universität Erlangen-Nürnberg Germany

ISBN: (纸本)9798350322231

The computational power of High-Performance Computing (HPC) systems is constantly increasing, however, their input/output (IO) performance grows relatively slowly, and their storage capacity is also limited. This unbalance presents significant challenges for applications such as Molecular Dynamics (MD) and Computational Fluid Dynamics (CFD), which generate massive amounts of data for further visualization or analysis. At the same time, checkpointing is crucial for long runs on HPC clusters, due to limited walltimes and/or failures of system components, and typically requires the storage of large amount of data. Thus, restricted IO performance and storage capacity can lead to bottlenecks for the performance of full application workflows (as compared to computational kernels without IO). In-situ techniques, where data is further processed while still in memory rather to write it out over the I/O subsystem, can help to tackle these problems. In contrast to traditional post-processing methods, in-situ techniques can reduce or avoid the need to write or read data via the IO subsystem. They offer a promising approach for applications aiming to leverage the full power of large scale HPC systems. In-situ techniques can also be applied to hybrid computational nodes on HPC systems consisting of graphics processing units (GPUs) and central processing units (CPUs). On one node, the GPUs would have significant performance advantages over the CPUs. Therefore, current approaches for GPU-accelerated applications often focus on maximizing GPU usage, leaving CPUs underutilized. In-situ tasks using CPUs to perform data analysis or preprocess data concurrently to the running simulation, offer a possibility to improve this underutilization. © 2023 IEEE.

关键词： graphics processing unit

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Research on 3D visualization technology of Dual-polarization Weather Radar Products 2021

Research on 3D Visualization technology of Dual-polarization...

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4th international conference on Data Science and Information Technology, DSIT 2021

作者： Wei, Haiwen Liu, Na Zhang, Qian Yang, Chuanfeng Guo, Junjian Wang, Shuo Shandong Meteorological Observatory China

ISBN: (纸本)9781450390248

Abstract: In order to solve the problem of the lack of geometric and topological information of in the three-dimensional display of the Dual-polarization Weather Radar products, using the Python library functions and computer graphics interpolation technology to analysis and coordinate transformation of the Dual-polarization products and ZDR,KDP and CC drawn in three-dimensional modeling. Compared the elevation-by-elevation products of ZDR,KDP and CC with the single elevation plane products, draw a three-dimensional dual-polarization radar product echo map. The 3D visualization products can show the spatial distribution of echo more intuitively and comprehensively, help to obtain the overall structure information of echo, and provide important basis and model for severe weather monitoring and early warning, provide feasible ideas for the international problem of radar stereo imaging. © 2021 ACM.

关键词： Three dimensional displays

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The Research Landscape of Site-Specific Art in Public Art Map Quantification Based on Citespace 12th

The Research Landscape of Site-Specific Art in Public Art Ma...

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12th international conference on Image and graphics, ICIG 2023

作者： Zhang, Yun Kim, Cheeyong Department of Storytelling Graduate School Dong-Eui University Seoul Korea Republic of College of ICT Digital Contents Game Engineering University Seoul Korea Republic of

ISBN: (纸本)9783031463105

Public art has attracted attention from researchers in various fields due to its wide research scope. However, there has been relatively little research on specific fields within the development process of public art and specific artistic phenomena in these fields. Understanding and grasping the context of this phenomenon from a macro perspective is not an easy task. This paper utilizes the advantages of Citespace, a literature-based visualization software, to conduct data visualization analysis on research literature in the specific field of public art over the past two *** results show that: (1) The number of publications on specific fields within public art in both the Web of Science (WOS) and CNKI (China National Knowledge Infrastructure) platforms has experienced two stages of research. (2) By analyzing the cooperation networks of authors and research institutions, the research status and influence of national institutions and journals on this topic in the last 20 years can be observed. The research institutions on the WOS platform exhibit a pattern of broad collaboration and exchange, while those on the CNKI platform tend to have smaller group collaborations. (3) Through keyword clustering analysis, nine clusters were identified. On the WOS platform, they were summarized into two main research directions: the specificity of public art locations and their relationship with art, and the practical approaches within specific fields of public art. On the CNKI platform, they were summarized into three main research directions: public art and publicness, the regional nature of specific fields, and the artistic forms within specific fields. (4) Based on the high-frequency keyword table and keyword timeline graph, research content and trends on the WOS platform focus more on identity, cultural heritage, location, contemporary art, community, and other related research questions. On the CNKI platform, more attention is given to research questions about publicnes

关键词： Data visualization

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Face features-based personality assessment 15

Face features-based personality assessment

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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： Singh, Krishna Kumar Chiranjeevi, Sadu Sivalal, Kethavath Dept. of Computer Science and Engineering RGUKT Nuzvid Nuzvid521 202 India Dept. of Electronics and Communication Engineering RGUKT Nuzvid Nuzvid521 202 India

ISBN: (纸本)9789898704320

Personality assessment has been widely used in the professional psychology and signal processing fields. Recently, it has been a great interest from the computer vision research community in assessing personality from visual data. Many state-of-the-art models are assigned the Big-Five personality indicators using either external judges or personal interviews. We propose Face Features-based Personality Assessment (FFPA) that assesses the personality of a person based on one's facial features. It maps facial appearance into the Big-Five personality indicators, namely Extraversion, Agreeableness Conscientiousness, Neuroticism and Openness. The geometry-based and appearance-based approaches are used to extract features from the face and mapped to the personality indicators using Partial Least Square Regression (PLSR). The corresponding personality indicator values are collected by filling the online form of the Big-Five personality assessor. The computational experiments are performed on a synthetic dataset, consisting of the face images of 200 students. The experimental results show that the proposed model predicts the personality indicators with 0.95 coefficient of determination (approx.) and Mean Squared Error (MSE) is 0.001 (approx.). © 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： Mean square error

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Autism Spectrum Disorder Detection Using Convolutional Neural Network

Autism Spectrum Disorder Detection Using Convolutional Neura...

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

作者： V. Angel Petricia Jacksy M Bhavadharani R Dept. of Computer Science and Engineering St. Joseph's Institute of Technology Chennai

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Autism Spectrum Disorder(ASD) is a complex neurodevelopmental condition marked by challenges in social interaction, communication, and repetitive behaviors. Early detection is critical to enable timely intervention and improve outcomes for individuals with ASD. This research proposes an innovative framework that integrates Convolutional Neural Networks (CNNs) with advanced data preprocessing techniques, facial imaging, and behavioral analysis to enhance the accuracy and efficiency of ASD diagnosis. Leveraging data augmentation and transfer learning, the model achieves robust performance with high sensitivity and specificity. The novelty of this approach lies in its ability to identify subtle facial and behavioral patterns indicative of ASD, using a multidisciplinary strategy that combines neuroimaging, machine learning, and real-time diagnostic feedback. By advancing beyond traditional methods, this comprehensive framework holds the potential to revolutionize early ASD detection, making it more accessible, scalable, and precise.

关键词： Neuroimaging Autism Visual analytics Face recognition Transfer learning imaging Data visualization Sensitivity and specificity Real-time systems Convolutional neural networks

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Smart city solutions for location tracking 15

Smart city solutions for location tracking

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作者： Bhati, Neetesh Shetty, Sujala D. Raj, Aparna Department of Computer Science Birla Institute of Technology and Science Pilani India

ISBN: (纸本)9789898704320

With the advancement in technology cities are getting smarter and becoming more livable and responsive. In the next few years, we expect a significant rise in the use of data and technology to make better decisions and improve the quality of life. Outdoor navigation using GPS is relatively easy but finding way indoors is still considered as a frenetic task. We aim to use data from multiple sources to create a detailed profile of the geographic information for every individual which can be easily used and securely accessed whenever needed. In this paper, we propose a method for indoor navigation which guides the user to a specific spot using smart phones. Here A* algorithm is used to find the shortest path between two points on the map and ArcGIS software for creating the map data. The generated map along with the required services are hosted on Osiris, an open-source indoor map rest API server. The sever is connected to a front end using an Android application developed with Android Studio. This can be applied across large companies which are situated in sprawling campuses. © 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： Geographic information systems

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Report on estimating rice field quality using artificial intelligence 15

Report on estimating rice field quality using artificial int...

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作者： Khatraty, Yahjeb Bouha Nauwynck, Nedra Mellouli Diallo, Mamadou Tourad Nanne, Mohamedade Farouk University of Paris 8 - Vincennes - Saint-Denis Doctoral School Cognition Language Interaction Paris France University of Nouakchott Al-Aasriya Faculty of Science and Technology Doctoral School of Computer Science Nouakchott Mauritania

ISBN: (纸本)9789898704320

The use of artificial intelligence has made life easier for farmers, as analysis of agricultural data allows farmers to make informed decisions, supported by large data sets and processed by machine learning algorithms. In this paper, we present the literature on rice quality assessment according to the different criteria and factors used to predict the quality or yield of rice. Thus, we provided a list of machine learning and deep learning models that had high accuracy in predicting rice yield and quality. In addition, due to the lack of literature of a real-time rice field monitoring system, we proposed a real-time rice field condition monitoring system that collects weather and soil condition data and sends them to the web server. The farmer can see the status of its remotely field and can automate certain tasks such as irrigation based on the collected data values. © 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： Internet of things

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A Survey of 3D Gaussian Splatting: Optimization Techniques, Applications, and AI-Driven Advancements

A Survey of 3D Gaussian Splatting: Optimization Techniques, ...

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), international conference

作者： Santosh Reddy P Abhiram H K S Archish Department of Computer Science Engineering B.N.M. Institute of Technology Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

3D Gaussian Splatting (3DGS) has emerged as a transformative technique for real-time, high-quality 3D rendering. This paper surveys the advancements in 3DGS, focusing on optimization strategies, applications across diverse domains, and AI-driven innovations that enhance its utility. Optimization techniques, such as Mini-Splatting and sparsification frameworks, address challenges like computational overhead and memory inefficiency while maintaining visual fidelity. AI has further expanded the capabilities of 3DGS through frameworks like SceneTeller, ART3D and GaussianEditor, enabling text-to-3D generation, object-level manipulation, and artistic scene creation with multi-view consistency. Applications of 3DGS range from autonomous driving and robotics to virtual and augmented reality, highlighting its adaptability and efficiency. This survey underscores the importance of continued research to refine 3DGS’s scalability and applicability, solidifying its role at the intersection of computer graphics and artificial intelligence.

关键词： Surveys Technological innovation visualization Three-dimensional displays Scalability Rendering (computer graphics) Real-time systems Artificial intelligence Optimization Robots

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Research on Student Behavior Pattern Mining and Management System Based on Deep Learning

Research on Student Behavior Pattern Mining and Management S...

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Sensors, Electronics and computer Engineering (ICSECE), IEEE international conference on

作者： Shan Wang Shandong Vocational College of Science and Technology Weifang China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

According to the practice of students' work, the paper makes a statistical analysis of students' achievement, attendance, comprehensive quality and borrowing books. The kettle (ETL) is used to extract, purify, and transform the data, and it is loaded into the oracle database for storage and management, and various rule bases and algorithms are used to parse and the data. By using graphics, tables and other visual tools, an intelligent analysis platform for students' work under the environment of big data is established. The data structure and statistical method are used to express the user's behavior characteristics, obtain the specific behavior information, and build the behavior database according to the specific time-granulated way. This project proposes a clustering mining method based on behavioral characteristics based on behavioral data sets. The research results show that the visualization platform of college students' behavior analysis built with big data can realize accurate diagnosis of students' learning situation, personalized learning analysis, intelligent analysis and decision making, and early warning of disciplinary violations. It greatly improves the teaching quality of the school and achieves the purpose of “teaching students according to their aptitude”.

关键词： visualization Statistical analysis Databases Education Data visualization Transforms Big Data Sensors Data mining Indexes

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