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

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19th Chinese conference on Image and graphics Technologies and Applications, IGTA 2024

19th Chinese Conference on Image and Graphics Technologies a...

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19th Chinese conference on Image and graphics Technologies and Applications, IGTA 2024

ISBN: (纸本)9789819799183

The proceedings contain 31 papers. The special focus in this conference is on Image and graphics Technologies and Applications. The topics include: Optimized Recognition and Depth Estimation for Fruit Picking Robots;BM3D-UGanNet: A Hybrid Deep Learning Network for Low-Light Thangka Image Enhancement;stagewise Positional Encoding for Implicit Neural Representation of Image;image Enhancement Based on a Diffusion Model Guided by No-Reference Image Quality Assessment;adaptive Pixel Pair Generation Strategy for Image Matting Methods Based on Pixel Pair Optimization;EdgCNN: Thangka Line Drawing Extraction Based on CNN;fire Detection Based on Flame Enhancement for Weak Fires;HDR-TDC: High Dynamic Range imaging with Transformer Deformable Convolution;enhancing Fine-Tuning Performance of Text-to-Image Diffusion Models for Few-Shot Image Generation Through Contrastive Learning;generalized Diffusion Models for Non-gaussian Noise;phase Error Correction Algorithm Based on Complementary Gray Code and Reverse Error Compensation;defect Detection Based on Normalized Attention Mechanism and Multi-level Feature Fusion;Study on Different Apple Ripeness Detection Based on Improved YOLOv5;learning Features by Minimizing the Interframe Differences;VTR-Former: Vision Token Rolling Transformer for Weakly Supervised Temporal Text Localization;CMME-YOLO: Composite Microscale Multi-stream Enhanced Model for PCB Defect Detection;multi-behavior Recommendation with Hypergraph Contrastive Learning;contrastive Learning-Based Dual Path Fusion Network for Group Activity Recognition;microclimate Regulation in Glass Greenhouses: Simulation of Wind Velocity and Temperature Fields and Design Model of the Greenhouse Fans;visualization of Spatial and Temporal Information of Railway Industrial Heritage in Modern China;Exploration of New Energy Electric Vehicle Development Based on SSA-SVR Model;long Sequences Generation for Motion Diffusion Models;Gaussian Replacement: Gaussians-Mesh Joint Rendering for Rea

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RaNeuS: Ray-adaptive Neural Surface Reconstruction

RaNeuS: Ray-adaptive Neural Surface Reconstruction

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international conference on 3D imaging, Modeling, Processing, visualization and Transmission (3DIMPVT)

作者： Yida Wang David Joseph Tan Nassir Navab Federico Tombari Technische Universität München Google

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

Our objective is to leverage a differentiable radiance field e.g. NeRF to reconstruct detailed 3D surfaces in addition to producing the standard novel view renderings. There have been related methods that perform such tasks, usually by utilizing a signed distance field (SDF). However, the state-of-the-art approaches still fail to correctly reconstruct the small-scale details, such as the leaves, ropes, and textile surfaces. Considering that different methods formulate and optimize the projection from SDF to radiance field with a globally constant Eikonal regularization, we improve with a ray-wise weighting factor to prioritize the rendering and zero-crossing surface fitting on top of establishing a perfect SDF. We propose to adaptively adjust the regularization on the signed distance field so that unsatisfying rendering rays won’t enforce strong Eikonal regularization which is ineffective, and allow the gradients from regions with well-learned radiance to effectively back-propagated to the SDF. Consequently, balancing the two objectives in order to generate accurate and detailed surfaces. Additionally, concerning whether there is a geometric bias between the zero-crossing surface in SDF and rendering points in the radiance field, the projection becomes adjustable as well depending on different 3D locations during optimization. Our proposed RaNeuS 1 are extensively evaluated on both synthetic and real datasets, achieving state-of-the-art results on both novel view synthesis and geometric reconstruction. 1 Codes are released at https://***/wangyida/ra-neus.

关键词： Training Surface reconstruction Three-dimensional displays Rendering (computer graphics) Surface fitting Task analysis Image reconstruction

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Analysing the Nutritional Facts in Mc. Donald’s Menu Items Using Exploratory Data Analysis in R 5th

Analysing the Nutritional Facts in Mc. Donald’s Menu Items ...

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5th international conference on Emerging Technologies in computer Engineering: Cognitive Computing and Intelligent IoT, ICETCE 2022

作者： Vignesh, K. Nagaraj, P. Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Krishnankoil Virudhunagar India

ISBN: (纸本)9783031070112

A quantitative data analytic tradition is the Exploratory Data Analysis (EDA) based on the original work of John Tukey. In Statistics, EDA is the process of cleaning data and using appropriate visualizations to extract insights and summarize the data in the given dataset. The computational and core conceptual tools of EDA cover the use of interactive data display and graphics, diagnosing, evaluating, an emphasis on model building, and addressing the issues of the fundamental measurements that are consorted with several distributions and also undertaking some of the procedures that are resistant to mislead or flawed results because of the unpredictable change of real world data. EDA can be further classified as Graphical or non-graphical and Univariate or multivariate data. EDA can be helpful for expressing what does the data refers before the modeling task. It is not easy to see at a large dataset or a whole spreadsheet and to decide important characteristics of the data. It may be typical to obtain insights by seeing at plain numbers. So, EDA techniques have been evolved as an assist in this type of situation. In this article we are going to take a nutritional dataset and visualize it using EDA. This visualization contains Bar chart, Histogram, Boxplot, Scatterplot, Barcode and Violin plot. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multivariant analysis

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Improved 3D photon counting imaging using singular value decomposition (SVD)

Improved 3D photon counting imaging using singular value dec...

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international conference on Control, Automation and Systems ( ICCAS)

作者： Seungwoo Song Gilsu Yeo Hyun-Woo Kim Myungjin Cho Min-Chul Lee Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka City Fukuoka Japan School of ICT Robotics and Mechanical Engineering IITC Hankyoung National University Anseong Republic of Koera

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In this paper, we propose improved three-dimensional (3D) photon counting imaging using singular value decomposition (SVD). In conventional 3D photon counting imaging can visualize 3D image under photon-starved conditions. However, the conventional method has problems that it may not visualize 3D image under extremely photon-starved conditions and the quality of visualized image may be degraded. To solve this problem, we apply SVD to image before applying the photon counting integral imaging in this paper. To verify feasibility of our method, we implement experiments and show the experimental results. In addition, for numerical comparison, the image quality assessment methods such as structural similarity index map (SSIM) and blind/referenceless image spatial quality evaluator (BRISQUE) are calculated.

关键词： Image quality visualization Three-dimensional displays Image resolution Noise Indexes Image reconstruction Photonics Singular value decomposition Meteorology

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Deep Light Direction Reconstruction from single RGB images 29

Deep Light Direction Reconstruction from single RGB images

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29th international conference in Central Europe on computer graphics, visualization and computer Vision, WSCG 2021

作者： Miller, Markus Nischwitz, Alfred Westermann, Rüdiger Dept. of Computer Science and Mathematics University of Applied Sciences Munich Lothstr. 64 Bavaria MunichD-80335 Germany Chair of Computer Graphics and Visualization Technical University Munich Boltzmannstr. 3/II Bavaria GarchingD-85748 Germany

ISBN: (纸本)9788086943343

In augmented reality applications, consistent illumination between virtual and real objects is important for creating an immersive user experience. Consistent illumination can be achieved by appropriate parameterisation of the virtual illumination model, that is consistent with real-world lighting conditions. In this study, we developed a method to reconstruct the general light direction from red-green-blue (RGB) images of real-world scenes using a modified VGG-16 neural network. We reconstructed the general light direction as azimuth and elevation angles. To avoid inaccurate results caused by coordinate uncertainty occurring at steep elevation angles, we further introduced stereographically projected coordinates. Unlike recent deep-learning-based approaches for reconstructing the light source direction, our approach does not require depth information and thus does not rely on special red-green-blue-depth (RGB-D) images as input. © 2021 University of West Bohemia. All rights reserved.

关键词： Image reconstruction

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Research on ISAR Imagine of High Frequency Ground Wave Radar in Large Sea Scene

Research on ISAR Imagine of High Frequency Ground Wave Radar...

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international conference on computer and Communications (ICCC)

作者： Jiahong Peng Conghui Qi Han Luo Youkun Xu Guizhou Aerospace Institute of Metrology & Test Guiyang China School Of Electrical Engineering and Electronic Information Xihua University Chengdu China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

High frequency ground wave radar (HF-GWR) is considered as a new and effective technical tool for marine environmental monitoring because of its advantages of beyond visual range, large range and low cost, meanwhile, ISAR (Inverse synthetic Aperture radar) imaging technology has great application value in the strategy of maritime power. In this paper, PM sea spectrum and linear filtering method were used to simulate the wind driven sea surface, and combined with the digital elevation model (DEM), a large sea scene where the island target and the sea surface are combined is successfully constructed. Then, high-frequency numerical electromagnetic calculation method was used to obtain the broadband and large angle echo data of the sea scene. Finally, the echo data are processed by Simpson integral, and the 2D ISAR image of large sea scene with high/low extreme sea conditions at low sweep angle and high frequency band (working conditions of HF-GWR) is obtained successfully. The imaging results show that the contour of island targets and strong scattering points such as ridge lines can be clearly displayed under extreme sea conditions, which has a reference significance for the application of distributed/mobile HF-GWR in 2D ISAR imaging engineering of large sea scene.

关键词： Sea surface visualization Maximum likelihood detection Spaceborne radar imaging Scattering Radar Radar imaging High frequency Surface treatment

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Interactive Hyperspectral imaging Data visualization: A Catalyst for Sustainable Horticultural Practices with Artificial Intelligence

Interactive Hyperspectral Imaging Data Visualization: A Cata...

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Disruptive Technologies (ICDT), international conference on

作者： Minal Bafna Hina Singh Kaushal Kumar Amit Vinay Kumar Singh Jagendra Singh Department of Physics Agrawal P G College Jaipur India Department of CSE Ajay Kumar Garg Engineering College Ghaziabad India Department of Computer Science (AI & ML) Raj Kumar Goel Institute of Technology Ghaziabad India Department of Computer Science IMS Engineering College Ghaziabad India School of Computer Science & Engineering Lovely Professional University Jalandhar India School of Computer Science Engineering and Technology Bennett University Greater Noida India

This work investigates the revolutionary potential of AI-powered interactive visualisation for sustainable horticulture practises. The amount of spectrum data provided by hyperspectral photography on the Earth's surface enables the observation and analysis of various phenomena that are vital to environmentally sustainable land use, agriculture, and research. However, there are numerous obstacles in handling and analysing the massive amounts of complex data provided by hyperspectral sensors. To address these issues, our study culminated in the development of an AIdriven interactive visualisation system that enables users to rapidly extract relevant information from hyperspectral data. The framework delivers great dependability in the interpretation of complicated hyperspectral data, with outstanding recall, accuracy, precision, and F1 score values. Furthermore, based on our statistics, user engagement scores show how well the framework engages users. The framework's utility and applicability are proved by the effects it has on decision-making, user happiness, and visual clarity. Our research shows that combining AI and hyperspectral imaging can improve horticulture practises and encourage resource- and environmentally-friendly ways, which has substantial practical implications. By using this strategy, growers and environmental scientists can avoid resource waste, make datadriven decisions, and ameliorate the negative environmental effects of horticulture practises.

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User, customer and consumer experience: Highlighting the heterogeneity in the literature 16

User, customer and consumer experience: Highlighting the het...

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16th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2021

作者： Sellier, Quentin Poncin, Ingrid Vanderdonckt, Jean Louvain Research Institute in Management and Organizations UCLouvain Place des Doyens Louvain-la-Neuve Belgium

ISBN: (纸本)9789897584886

The notion of experience has gained in popularity both in management and in computer science. To assess the quality of an information system, specialists in human-computer interaction are now referring to the user experience. On the marketing side, the concept of experience has also become key to describe the relationship between an individual and a brand. Several streams of research exist, some privileging the notion of customer experience and others of consumer experience. However, the multiplication of those works also created fragmentation and theoretical heterogeneity, as emerged through our analyses. This situation is particularly noxious to the communication between the disciplines of human-computer interaction and marketing, becoming more and more necessary. In order to promote this multidisciplinary communication, we clearly define and differentiate the constructs of experience. We also highlight the current heterogeneity in the literature through a systematic literature review and we end by formulating some suggestions to researchers and practitioners. This work contributes to a better communication between the disciplines of human-computer interaction and marketing, and more particularly to the unification of the constructs of experience. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Human computer interaction

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Fracture Detection in X-Ray Images Using Whale Optimization Algorithm-Enhanced Bi-Directional LSTM Networks

Fracture Detection in X-Ray Images Using Whale Optimization ...

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international conference on System Modeling & Advancement in Research Trends (SMART)

作者： Raj Gaurang Tiwari Mahesh Manchanda Ambuj Kumar Agarwal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Dehradun Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science and Engineering Sharda School of Engineering and Technology Sharda University Greater Noida India

ISBN: (数字)9798350380583

ISBN: (纸本)9798350380590

Rapid and reliable fracture detection in X-ray images is essential for medical diagnosis. This research offers a hybrid deep learning strategy that leverages the Whale Optimization Algorithm (WOA) to choose the most significant features from AlexNet and ResNet50. WOA enhances feature selection by searching for relevant attributes. To identify fractures, a Bi-directional Long Short-Term Memory (Bi-LSTM) network is employed. The proposed hybrid fracture diagnosis method beats existing methods with 96.86% accuracy. Integration of optimization approaches with powerful deep-learning architectures may improve medical imaging diagnosis accuracy.

关键词： Deep learning visualization Accuracy Soft sensors Feature extraction Whale optimization algorithms Optimization X-ray imaging Standards Residual neural networks

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An Efficient Hybrid Deep Learning Model for Detecting Musculoskeletal Abnormalities

An Efficient Hybrid Deep Learning Model for Detecting Muscul...

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Computational, Communication and Information Technology (ICCCIT), international conference on

作者： Arpit Deo Priyasha Gupta Karnika Deveradi Kashish Patidar Ashish Kumawat Pankaj Malik Department of Computer Science and Engineering Medi-Caps University Indore Madhya Pradesh India Department of Computer Engineering Institute of Engineering & Technology Devi Ahilya Vishwavidyalaya Indore Madhya Pradesh India

ISBN: (数字)9798331512965

ISBN: (纸本)9798331512972

Deep Convolutional Neural Networks (DCNNs) have made tremendous advances in healthcare, but their limited perceptual capacities make it difficult to capture extensive structural details. To solve this restriction, this study presents a new technique which integrates the benefits of EfficientNet to perform local data extraction with DenseNet201 for processing global characteristics in pictures. The MURA dataset, which contains 40,005 radiographic pictures, is used in the project with the goal of enhancing radiographic image categorization, notably for identifying Musculoskeletal disorders. The goal of the project is to accomplish a more thorough analysis of radiological pictures by successfully collecting global as well as local information via the fusion of EfficientNet and DenseNet201. The proposed approach shows positive outcomes, with the combined approach obtaining an overall accuracy of 96.38% on the test dataset and a sensitivity of 0.90.

关键词： Musculoskeletal system visualization Sensitivity Accuracy Sensitivity and specificity Image categorization Information and communication technology Diagnostic radiography Medical diagnostic imaging Extremities

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