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

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14th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2019

14th International Joint Conference on Computer Vision, Imag...

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14th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2019

ISBN: (纸本)9783030415891

The proceedings contain 25 papers. The special focus in this conference is on computer Vision, imaging and computer graphics Theory and Applications. The topics include: visualization of Tree-Structured Data Using Web Service Composition;breaking the Curse of Visual Analytics: Accommodating Virtual Reality in the visualization Pipeline;designing a Visual Analytics System for Medication Error Screening and Detection;a Layered Approach to Lightweight Toolchaining in Visual Analytics;fast Approximate Light Field Volume Rendering: Using Volume Data to Improve Light Field Synthesis via Convolutional Neural Networks;A Reproducibility Study for Visual MRSI Data Analytics;a Self-regulating Spatio-Temporal Filter for Volumetric Video Point Clouds;modeling Trajectories for 3D Motion Analysis;quantitative Comparison of Affine Feature Detectors Based on Quadcopter Images;An MRF Optimisation Framework for Full 3D Reconstruction of Scenes with Complex Reflectance;synthesising Light Field Volume Visualisations Using Image Warping in Real-Time;Robustifying Direct VO to Large Baseline Motions;localization and Grading of Building Roof Damages in High-Resolution Aerial Images;semantic Image Completion Through an Adversarial Strategy;an Enhanced Louvain Based Image Segmentation Approach Using Color Properties and Histogram of Oriented Gradients;Vehicle Activity Recognition Using DCNN;quantifying Deformation in Aegean Sealing Practices;motion Capture Analysis and Reconstruction Using Spatial Keyframes;involving Hearing, Haptics and Kinesthetics into Non-visual Interaction Concepts for an Augmented Remote Tower Environment;virtual Reality System for Ship Handling Simulations: A Case Study on Nautical Personnel Performance, Observed Behaviour, Sense of Presence and Sickness;A Process Reference Model for UX;AAT Meets Virtual Reality.

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Artificial Intelligence Based Segmentation for Skin-Layer visualization from Optical Coherence Tomography Images

Artificial Intelligence Based Segmentation for Skin-Layer Vi...

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IEEE international conference on Consumer Electronics (ICCE)

作者： Gilang Titah Ramadhan Yori Pusparani Ardha Ardea Prisilla Wei-Cheng Shen Hsu-Tang Cheng Ben-Yi Liau Yih-Kuen Jan Wen-Thong Chang Chih-Yang Lin Chi-Wen Lung Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Visual Communication Design Budi Luhur University Jakarta Indonesia Department of Digital Media Design Asia University Taichung Taiwan Department of Fashion Design LaSalle College Jakarta Jakarta Indonesia Department of Creative Product Design Asia University Taichung Taiwan Division of Plastic Surgery Asia University Hospital Taichung Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Department of Kinesiology and Community Health University of Illinois Urbana USA Department of Mechanical Engineering National Central University Taoyuan Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Changes in epidermal thickness are linked to various skin diseases, such as diabetic foot. Optical Coherence Tomography (OCT), a noninvasive imaging technology, enables detailed visualization of skin layers. This study employed a deep learning approach using the U-Net architecture to analyze OCT images, specifically focusing on the stratum corneum (SC) and epidermis (ED) layers. Utilizing a dataset of 10,000 images, the U-Net model achieved 92 % accuracy in predicting SC and 95% accuracy for ED. These results highlight the potential of this method for accurate 3D visualization of SC and ED layers, paving the way for precise assessment of skin layer thickness and its changes in medical applications.

关键词： Deep learning visualization Solid modeling Image segmentation Accuracy Three-dimensional displays Optical coherence tomography Medical services Predictive models Epidermis

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

16th International Joint Conference on Computer Vision, Imag...

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

ISBN: (纸本)9783031254765

The proceedings contain 16 papers. The special focus in this conference is on computer Vision, imaging and computer graphics Theory and Applications. The topics include: Towards Interactive Geovisualization Authoring Toolkit for Industry Use Cases;global-first Training Strategy with Convolutional Neural Networks to Improve Scale Invariance;spline-Based Dense Medial Descriptors for Image Simplification Using Saliency Maps;BS-GAENets: Brain-Spatial Feature Learning Via a Graph Deep Autoencoder for Multi-modal Neuroimaging Analysis;enhancing Backlight and Spotlight Images by the Retinex-Inspired Bilateral Filter SuPeR-B;Rethinking RNN-Based Video Object Segmentation;facade Layout Completion with Long Short-Term Memory Networks;generating Haptic Sensations over Spherical Surface;effects of Emotion-Induction Words on Memory and Pupillary Reactions While Viewing Visual Stimuli with Audio Guide;a Bimanual Flick-Based Japanese Software Keyboard Using Direct Kanji Input;comparison of Cardiac Activity and Subjective Measures During Virtual Reality and Real Aircraft Flight;improving Self-supervised Dimensionality Reduction: Exploring Hyperparameters and Pseudo-Labeling Strategies;visualization of Source Code Similarity Using 2.5D Semantic Software Maps;revisiting Order-Preserving, Gap-Avoiding Rectangle Packing.

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TriFormer: Triple Branch Heterogeneous Transformers for UHD Image Restoration

TriFormer: Triple Branch Heterogeneous Transformers for UHD ...

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

作者： Xinchen Ma Yue Lu School of Communication and Electronic Engineering East China Normal University Shanghai China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Ultra-high-definition (UHD) image restoration is becoming a critical research area due to the increasing demand for high-quality visual content in various applications, including autonomous driving, remote sensing, digital entertainment, etc. However, UHD image restoration tasks present notable challenges, including the significant computational burden posed by the large image size scale, the difficulty in preserving fine details and textures, and the increased susceptibility to noise and artifacts during the restoration process. In this paper, we propose a novel triple-branched optimized heterogeneous transformer for UHD image restoration, named TriFormer. Specifically, our method embeds a high-resolution CNN branch for high-frequency features, a low-resolution pixel-wise attention branch for low-frequency features, and a channel-wise attention branch for feature fusion. We perform experiments across two UHD image restoration tasks: enhancing low-light images and deblurring. Results demonstrate that our model outperforms state-of-the-art approaches both quantitatively and qualitatively. The code will be made available at https://***/Chloe-mxxxxc/TRIFORMER.

关键词： visualization Technological innovation Noise graphics processing units Entertainment industry computer architecture Transformers Image restoration Speech processing Remote sensing

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Enhanced Image Steganography Using Neural Style Transfer

Enhanced Image Steganography Using Neural Style Transfer

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), international conference on

作者： Nithiyanantham Vijaya Lakshmi A Dinesh S Roshan R Department of Computer Science Sri Sivasubramaniya Nadar College of Engineering Chennai India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

This paper presents a novel approach to image steganography by integrating Neural Style Transfer (NST) with multi-layer embedding techniques. Traditional steganography methods often struggle with the fundamental challenges of limited data capacity and image quality degradation when embedding large volumes of data. Also traditional methods fail to accurately retrieve the secret data at the receiving end and the methods are vulnerable to steganalysis *** system transcends these limitations through a three-module design: a multi-layer embedding module based on LSB method over RGB channels, a Neural Style Transfer module for aesthetic processing, and a Style Generative Adversarial Network (StyleGAN) for preservation of image fidelity. The multi-layer embedding scheme boosts data capacity significantly without loss of visual quality, and NST provides an additional layer of security by hiding secret information naturally within stylized transformations. Experimental results demonstrate that our method provides higher embedding capacity compared to traditional methods without loss of imperceptibility through aesthetic processing. The addition of StyleGAN also enhances visual quality of stego images, rendering them steganalysis-immune. Our method is highly promising in applications where secure transmission of large data is necessary, with correct recovery of data without loss of aesthetic quality of the cover image.

关键词： Image quality Degradation Steganography visualization Data security Generative adversarial networks Rendering (computer graphics) Neural style transfer Robustness Telecommunication computing

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Color imaging in Medical Video Systems: Problems and Features

Color Imaging in Medical Video Systems: Problems and Feature...

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Digital Signal Processing and its Applications (DSPA), international conference on

作者： Natalia A. Obukhova Alexandr A. Motyko Alexandr A. Pozdeev Konstantin A. Smirnov SPbSU ETU “LETI” St. Petersburg Russia

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper explores the issue of accurate colour reproduction in medical imaging. It considers key problems and lists standards related to the process of forming and displaying medical images. Particular attention is paid to the fact that the existing standards do not take into account the individual characteristics of colour perception in different doctors. In the conditions of using modern displays with wide colour coverage this can lead to errors in colour rendering for a particular doctor, which, in turn, reduces the accuracy of disease diagnostics. The application of optimal LUT (Look-Up Table) with variable resolution to recalculate the colour space of the display is proposed, which allows to personalise the image for individual features of the doctor's vision and improve the accuracy of diagnosis. Experimental results demonstrating the advantages of the proposed approach over classical colour transform methods are presented. The results confirm that the use of variable resolution LUT can reduce colour rendering errors and improve the quality of medical diagnostics.

关键词： Image resolution Accuracy Three-dimensional displays Image color analysis Transforms Observers Rendering (computer graphics) Table lookup Standards Signal resolution

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An Improved Nimble Filter for Medical Image Sharpening

An Improved Nimble Filter for Medical Image Sharpening

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), international conference on

作者： Eswar R B Vishnukumar S Sabu M K Neena Shilen Department of Computer Applications Cochin University of Science and Technology Kochi Kerala India Department of Developmental Pediatrics Sun Rise Hospital Kochi Kerala India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Medical image sharpening is crucial for enhancing diagnostic accuracy and visual clarity. This paper proposes an Improved Nimble Filter, an advancement over the standard Nimble Filter, designed to improve the sharpness and detail in medical images. The proposed filter incorporates an adaptive window size, a lower tuning weight that adapts to local image characteristics, and a local Otsu thresholding step to refine the sharpening process. Additionally, the filter applies a Gaussian blur to the local region of interest to reduce noise and preserve edges. These enhancements enable effective edge preservation and noise minimisation, addressing the limitations of existing sharpening techniques. The effectiveness of the Improved Nimble Filter is demonstrated through comparative analysis with other well-known methods, including the Laplacian operator, unsharp mask, shock filter, and generalised unsharp masking, using Brain MRI images from the ABIDE dataset. Experimental results show that the proposed filter significantly outperforms these techniques in terms of visual quality, edge preservation, and processing times, making it a valuable tool for medical image processing applications.

关键词： visualization Thresholding (imaging) Laplace equations Image edge detection Magnetic resonance imaging Noise Minimization Tuning Medical diagnostic imaging Standards

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Cooperative Neural Radiance Field for Dynamic Scene Deblurring

Cooperative Neural Radiance Field for Dynamic Scene Deblurri...

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

作者： Dong Liu Zhiyong Wang Linlin Guo Shandong Youth University of Political Science Shandong Normal University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recent advancements in 3D dynamic scene reconstruction from monocular videos offer novel possibilities for space-time view synthesis. However, video blurriness caused by defocus or motion commonly seen in real-world scenarios can degrade the synthesis quality. Addressing this challenge, we propose an innovative approach that integrates a deformable blurring kernel with ray origin prediction into neural scene flow fields. This integration effectively models the blurriness inherent in the imaging process. Moreover, we introduce the Cooperative Neural Radiance Field (CoopNeRF), which explicitly simulates defocus blur by incorporating bokeh rendering within the physical blurring framework. Our comprehensive experiments are conducted on six various synthesized datasets, which demonstrate that our method significantly outperforms existing techniques and provides superior quantitative results. Our proposed CoopNeRF not only enhances the synthesis quality but also broadens the applicability of 3D reconstruction techniques in real-world scenarios.

关键词： Three-dimensional displays Dynamics imaging Signal processing Rendering (computer graphics) Neural radiance field Kernel Speech processing Image reconstruction Videos

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VISIGRAPP 2018 - Proceedings of the 13th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications

VISIGRAPP 2018 - Proceedings of the 13th International Joint...

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13th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2018

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Proceedings of IMTA-5 2015 - 5th international Workshop on Image Mining. Theory and Applications, in conjunction with the 10th Internatioanal Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2015

Proceedings of IMTA-5 2015 - 5th International Workshop on I...

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5th international Workshop on Image Mining. Theory and Applications, IMTA-5 2015 - In conjunction with the 10th Internatioanal Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2015

ISBN: (纸本)9789897580949

The proceedings contain 15 papers. The topics discussed include: development of the logic programming approach to the intelligent monitoring of anomalous human behaviour;location of pupil contour by Hough transform of connectivity components;testing an image mining approach to obtain pressure ulcers stage and texture;on image representing in image analysis;a variational method to remove the combination of Poisson and Gaussian noises;PRIAR using a graph segmentation method;virtual immersive environments for underwater archaeological exploration;current trends in mathematical image analysis - a survey;human pose estimation in video via MCMC sampling;signal processing for underwater archaeology;experimenting an embedded-sensor network for early warning of natural risks due to fast failures along railways;selective use of optimal image resolution for depth from multiple motions based on gradient scheme;and blood flow prediction and visualization within the aneurysm of the middle cerebral artery after surgical treatment.

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