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

共 12047 条记录，以下是351-360 订阅

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Photoacoustic imaging using Diode Laser for Soft Tissue visualization 14

Photoacoustic Imaging using Diode Laser for Soft Tissue Visu...

引用

14th international Symposium on Modern Optics and Its Applications, ISMOA 2023

作者： Tasmara, Fikhri A. Wahyuni, Eka Silalahi, Harry M. Widyaningrum, R. Setiawan, A. Mitrayana Department of Physics Universitas Gadjah Mada Indonesia Department of Applied Physics Tunghai University Taiwan Department of Dentomaxillofacial Radiology Universitas Gadjah Mada Indonesia Department of Physics Universitas Kristen Satya Wacana Indonesia

This study aimed to develop a photoacoustic imaging system using a diode laser as a radiation source, and a condenser microphone as a soft-tissue image detector. These tools were set in a static position and combined with the mechanic component to move the object table in the X-Y direction and were controlled by a computer with a LabView program. The result showed the built photoacoustic imaging system was used to analyze soft tissue using a diode laser in the frequency range of over 15 kHz with a 24%-47% duty cycle modulation. Furthermore, the minimum shift of the mechanic component X-Y stage was 0.02 mm, the sampling data rate was 1 second/pixel, and the image showed soft tissue intensity is generally higher than non-biological materials. © Published under licence by IOP Publishing Ltd.

关键词： Semiconductor lasers

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Prototype Transferred Diverse Features for Day-night Cross-domain Facial Expression Recognition 16

Prototype Transferred Diverse Features for Day-night Cross-d...

引用

2024 16th international conference on graphics and Image Processing, ICGIP 2024

作者： Ma, Teng Qi, Yuhan Wang, ZhuoRan Li, YiPei Wang, Jiaxiang State Grid Corporation of Shanxi Province Shanxi 030025 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China Beijing Institute of Technology China Dublin International College Ireland

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

Facial Expression Recognition (FER) encounters significant challenges due to the limited sensitivity of visible light images in low light conditions. Most existing cross-domain emotion recognition studies have focused on domain adaptation for different visible light datasets, often neglecting the problem of emotion recognition under varying lighting conditions. To address this, we introduce the first cross-domain emotion recognition study for day and night environments, emphasizing the modal migration between normal visible light and low-light emotion maps. Considering the limited number of emotion maps and the reduced emotional detail in nighttime imaging, we designed an attention-switching diversified feature capture module to focus on facial expressions and extract more local emotional features that aid in migration. Given the significant domain shifts between samples in different lighting environments, we further developed a prototype feature transfer module to learn modality-independent category features and reduce domain differences between visible and low-light features. To tackle the challenge of numerous low sentiment value samples in the dataset, we introduce a high-confidence blending module to filter informative visible and infrared samples for fusion, producing features that combine the styles of both domains. Compared to state-of-the-art methods in domain adaptation and cross-domain emotion recognition, our approach demonstrates superior performance and validates its effectiveness. © 2025 SPIE.

关键词： Emotion Recognition

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Double embedding reversible information hiding based on chunking 3

Double embedding reversible information hiding based on chun...

引用

3rd international conference on computer graphics, Image, and Virtualization, ICCGIV 2023

作者： Hui, Zi Wang, Gencheng Chen, Yuzhen Xizang Minzu University Information engineering institute Shaanxi 712082 China Xizang Minzu University Key Laboratory of Optical Information Processing and Visualization Technology Tibet Autonomous Region Shaanxi 712082 China Tibet Cyberspace Governance Research Base Shaanxi 712082 China

ISBN: (纸本)9781510671720

A reversible data hiding method based on double embedding in chunking is proposed for existing data hiding algorithms to improve the embedding capacity and generate a secret-laden image with a high visual effect. Firstly, the original image is chunked and different reversible embedding methods are applied to different parts of the sub-blocks for the secret information embedding operation. To improve the embedding capacity, the secret information continues the pre-processing operation and adopts a hierarchical embedding method to improve the utilization of each embeddable point. The original prediction method is also improved to generate a steeper error histogram with more embeddable pixel points. In addition, the use of a suitable prediction and embedding method produces a compensating reduction effect when performing double embedding, reducing the number of invalid displacements and improving the quality of the carrier image. It is experimentally verified that the proposed method outperforms some state-of-the-art RDH work with higher embedding capacity as well as lower distortion. For a standard Cameraman image, a peak signal-to-noise ratio of up to 67.11 dB can be obtained when the embedding capacity is 10000 bits. © 2023 SPIE.

关键词： Pixels

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Beyond the Benchmark: Detecting Diverse Anomalies in Videos 32

Beyond the Benchmark: Detecting Diverse Anomalies in Videos

引用

32nd international conference in Central Europe on computer graphics, visualization and computer Vision, WSCG 2024

作者： Arad, Yoav Werman, Michael The Hebrew University of Jerusalem Israel

Video Anomaly Detection (VAD) plays a crucial role in modern surveillance systems, aiming to identify various anomalies in real-world situations. However, current benchmark datasets predominantly emphasize simple, single-frame anomalies such as novel object detection. This narrow focus restricts the advancement of VAD models. In this research, we advocate for an expansion of VAD investigations to encompass intricate anomalies that extend beyond conventional benchmark boundaries. To facilitate this, we introduce two datasets, HMDB-AD and HMDB-Violence, to challenge models with diverse action-based anomalies. These datasets are derived from the HMDB51 action recognition dataset. We further present Multi-Frame Anomaly Detection (MFAD), a novel method built upon the AI-VAD framework. AI-VAD utilizes single-frame features such as pose estimation and deep image encoding, and two-frame features such as object velocity. They then apply a density estimation algorithm to compute anomaly scores. To address complex multi-frame anomalies, we add deep video encoded features capturing long-range temporal dependencies, and logistic regression to enhance final score calculation. Experimental results confirm our assumptions, highlighting existing models limitations with new anomaly types. MFAD excels in both simple and complex anomaly detection scenarios. © 2024 University of West Bohemia. All rights reserved.

关键词： computer Vision Smart Surveillance Systems Video Anomaly Detection

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Attention-Aware DAE for Automated Solar Coronal Loop Segmentation 32

Attention-Aware DAE for Automated Solar Coronal Loop Segment...

引用

32nd international conference in Central Europe on computer graphics, visualization and computer Vision, WSCG 2024

作者： Dhaubhadel, Prabal Man Lee, Jong Kwan Tian, Qing Dept. of Computer Science Bowling Green State University Bowling GreenOH43403 United States Dept. of Computer Science University of Alabama at Birmingham BirminghamAL35294 United States

This paper introduces an enhanced Denosing Autoencoder (DAE) model, incorporating a novel attention mechanism, for the segmentation of solar coronal loops. This work is based on DAE framework to address the segmentation challenges posed by intricate structures of coronal loops which also appear with other solar features and image noises. Specifically, we introduce Encoding-Aware Decoding Attention (EADA) to all decoding stages of DAE, which resulted in improvement in coronal loop segmentation. Our models are validated through experiments on a synthetic image dataset of 11,000 images and a test dataset of 165 real coronal images of the NASA’s Solar Dynamics Observatory (SDO) satellite mission. Compared to the state-of-the-art coronal loop segmentation baseline, our attention-enhanced model results in better loop gap-filling and higher segmentation metrics (i.e., 3.6% increase in accuracy, 11.4% better recall and 5.6% higher precision). © 2024 University of West Bohemia. All rights reserved.

关键词： NASA

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AI-Based Digital Twinning for Automated Joint 3D Scene Reconstruction and Semantic Enrichment

AI-Based Digital Twinning for Automated Joint 3D Scene Recon...

引用

ASCE international conference on Computing in Civil Engineering (I3CE)

作者： Wang, Tao Gan, Vincent J. L. Natl Univ Singapore Dept Built Environm Singapore Singapore

ISBN: (数字)9780784485231

ISBN: (纸本)9780784485231

Digital twin, with captured as-is information, provides potential for condition monitoring and inspection of the built environment. However, the state-of-the-art digital twin lacks a systematic approach to observing the environment and communicating information to the facility manager due to the incomplete data description capabilities. In addition, capturing as-built geometric information would enhance the digital twin towards smart facility management, but the current employment of 2D computer vision provides limited support to reflect the building conditions for maintenance management. Therefore, this paper presents an AI-based digital twinning approach for automated joint 3D scene reconstruction and semantic enrichment to incorporate the as-is information of the built environment. Two works are researched sequentially: the first concerns integrating BIM data schema with Sensor Model Language (SensorML) to enhance sensor description capability for assorted information queries, and the second focuses on an automated 3D reconstruction and defect detection to enrich digital twin with the as-is condition of the built environment. It is envisaged that the research will contribute to a new method to enhance the digital twin for the built environment including a scientific approach for data mapping between the BIM domain and sensing domain and a new framework for capturing accurate as-built geometric information on the digital twin.

关键词： Three dimensional computer graphics

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Exploring Machine Learning and Deep Learning for Brain Tumor Detection: A Review

Exploring Machine Learning and Deep Learning for Brain Tumor...

引用

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

作者： Vishwakarma, Uma Yadav, Pritaj Jain, Anurag Rabindranath Tagore University Department of Computer Science & Engineering M.P. Bhopal India

ISBN: (纸本)9798331521394

Brain tumor detection has emerged as a critical field of research, given the increasing incidence of tumors and their impact on patients' lives. Recent advancements in machine learning (ML) and deep learning (DL) have revolutionized medical imaging, offering enhanced accuracy and efficiency in diagnosing brain tumors. This review comprehensively explores various ML and DL techniques employed for brain tumor detection, with a focus on supervised and unsupervised learning methods. Key algorithms such as convolutional neural networks (CNNs), random forests, and support vector machines (SVMs) are evaluated in terms of their classification performance, segmentation capabilities, and diagnostic accuracy. Moreover, the paper highlights the role of pre-processing methods, feature extraction techniques, and the challenges of imbalanced datasets in achieving robust models. © 2025 IEEE.

关键词： Convolutional neural networks

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EasyPBR: A Lightweight Physically-based Renderer 16

EasyPBR: A Lightweight Physically-based Renderer

引用

16th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications (VISIGRAPP) / 16th international conference on computer graphics Theory and Applications (GRAPP)

作者： Rosu, Radu Alexandru Behnke, Sven Univ Bonn Autonomous Intelligent Syst Bonn Germany

ISBN: (纸本)9789897584886

Modern rendering libraries provide unprecedented realism, producing real-time photorealistic 3D graphics on commodity hardware. Visual fidelity, however, comes at the cost of increased complexity and difficulty of usage, with many rendering parameters requiring a deep understanding of the pipeline. We propose EasyPBR as an alternative rendering library that strikes a balance between ease-of-use and visual quality. EasyPBR consists of a deferred renderer that implements recent state-of-the-art approaches in physically based rendering. It offers an easy-to-use Python and C++ interface that allows high-quality images to be created in only a few lines of code or directly through a graphical user interface. The user can choose between fully controlling the rendering pipeline or letting EasyPBR automatically infer the best parameters based on the current scene composition. The EasyPBR library can help the community to more easily leverage the power of current GPUs to create realistic images. These can then be used as synthetic data for deep learning or for creating animations for academic purposes.

关键词： Physically-based Rendering Synthetic Data Generation visualization Toolkit

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3D gated imaging Using a Unet Model

3D gated Imaging Using a Unet Model

引用

2022 international conference on Automation, Robotics and computer Engineering, ICARCE 2022

作者： Zhang, Siqing Liu, Xiaoquan Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan China

ISBN: (纸本)9781665475488

Range gated 3D imaging is widely used in space imaging, distance measurement, automatic driving and other application scenarios. A range gated 3D imaging system based on neural network is proposed. The system inputs three range gated images through convolutional neural network, and then outputs a depth map. A single convolutional neural network is proposed to process range gated images, and a multi-scale loss function is used. The test results on the real data set of outdoor driving show that the model trained on the GPU(graphics processing unit) in this paper realizes range gated 3D imaging. © 2022 IEEE.

关键词： graphics processing unit

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Comparing Scatterplot Variants for Temporal Trends visualization in Immersive Virtual Environments 30

Comparing Scatterplot Variants for Temporal Trends Visualiza...

引用

30th IEEE conference Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Quijano-Chavez, Carlos Nedel, Luciana Freitas, Carla M. D. S. Univ Fed Rio Grande do Sul Porto Alegre RS Brazil

ISBN: (纸本)9798350348156

Trends are changes in variables or attributes over time, often represented by line plots or scatterplot variants, with time being one of the axes. Interpreting tendencies and estimating trends require observing the lines or points behavior regarding increments, decrements, or both (reversals) in the value of the observed variable. Previous work assessed variants of scatterplots like Animation, Small Multiples, and Overlaid Trails for comparing the effectiveness of trends representation using large and small displays and found differences between them. In this work, we study how best to enable the analyst to explore and perform temporal trend tasks with these same techniques in immersive virtual environments. We designed and conducted a user study based on the approaches followed by previous works regarding visualization and interaction techniques, as well as tasks for comparisons in three-dimensional settings. Results show that Overlaid Trails are the fastest overall, followed by Animation and Small Multiples, while accuracy is task-dependent. We also report results from interaction measures and questionnaires.

关键词： Human-centered computing visualization visualization design and evaluation methods Human-centered computing Human computer interaction (HCI) HCI design and evaluation methods User studies

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