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检索条件"任意字段=Proceedings of the 25th Spring Conference on Computer Graphics"

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DeepIcon: A Hierarchical Network for Layer-Wise Icon Vectorization 25

DeepIcon: A Hierarchical Network for Layer-Wise Icon Vectori...

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25th International conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Bing, Qi Zhang, Chaoyi Cai, Weidong School of Computer Science The University of Sydney NSW2006 Australia

ISBN: (纸本)9798350379037

In contrast to the well-established technique of rasterization, vectorization of images poses a significant challenge in the field of computer graphics. Recent learning-based methods for converting raster images to vector formats frequently suffer from incomplete shapes, redundant path prediction, and a lack of accuracy in preserving the semantics of the original content. these shortcomings severely hinder the utility of these methods for further editing and manipulation of images. To address these challenges, we present DeepIcon, a novel hierarchical image vectorization network specifically tailored for generating variable-length icon vector graphics based on the raster image input. Our experimental results indicate that DeepIcon can efficiently produce Scalable Vector graphics (SVGs) directly from raster images, bypassing the need for a differentiable rasterizer while also demonstrating a profound understanding of the image contents. © 2024 IEEE.

关键词： Vectors

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A toolkit of approaches for digital mapping and correction of visual distortion 23

A toolkit of approaches for digital mapping and correction o...

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25th International ACM SIGACCESS conference on computers and Accessibility (ASSETS)

作者： Ling, Ye Frohlich, David M. Williamson, Tom H. Guillemaut, Jean-Yves Univ Surrey Ctr Vis Speech & Signal Proc Guildford Surrey England Univ Surrey Digital World Res Ctr Guildford Surrey England St Thomas Hosp London England

ISBN: (纸本)9798400702204

Visual distortion, known as metamorphopsia, is a serious visual deficit with no effective clinical treatment and which cannot be corrected by traditional optical glasses. In this paper, we introduce a toolkit of approaches for digitally mapping and correcting visual distortion, that might eventually be incorporated in a low vision aid VR headset. We describe three different approaches spanning data-driven and generative designs and leveraging either uniocular or binocular cues. We present our proposed demonstrator, our evaluation roadmap, and challenges for the field. Initial tests with simulated data demonstrate the effectiveness of the approach. Once clinically validated, we hope these approaches will enable accurate mapping of visual distortion and eventually lead to the development of 'digital glasses' capable of correcting the effects of metamorphopsia and restoring healthy vision.

关键词： Visual distortion metamorphopsia computer graphics image warping corrective displays

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Dynamic View Synthesis of thin Structures with Short-term Movements from Monocular Videos Using Neural Radiance Fields 25

Dynamic View Synthesis of Thin Structures with Short-term Mo...

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25th International conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Rajapaksha, Uchitha Laga, Hamid Diepeveen, Dean Bennamoun, Mohammed Sohel, Ferdous School of Information Technology Murdoch University MurdochWA Australia The University of Western Australia Dept. of Computer Science and Software Engineering CrawleyWA Australia

ISBN: (纸本)9798350379037

Learning to generate motions of thin structures such as plant leaves in dynamic view synthesis is challenging. this is because thin structures usually undergo small but fast, non-rigid motions as they interact with air and wind. When given a set of RGB images or videos of a scene with moving thin structures as input, existing methods that map the scene to its corresponding canonical space for rendering novel views fail as the object movements are too subtle compared to the background. Disentangling the objects with thin parts from the background scene is also challenging when the parts show fast and rapid motions. To address these issues, we propose a Neural Radiance Field (NeRF)-based framework that accurately reconstructs thin structures such as leaves and captures their subtle, fast motions. the framework learns the geometry of a scene by mapping the dynamic images to a canonical scene in which the scene remains static. We propose a ray masking network to further decompose the canonical scene into foreground and background, thus enabling the network to focus more on foreground movements. We conducted experiments using a dataset containing thin structures such as leaves and petals, which include image sequences collected by us and one public image sequence. Experiments show superior results compared to existing methods. Video outputs are available at https://***/. © 2024 IEEE.

关键词： Rendering (computer graphics)

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Towards Developing a Voice-Over-Guided System for Visually Impaired People to Learn Writing the Alphabets 25

Towards Developing a Voice-Over-Guided System for Visually I...

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25th International conference on computer and Information Technology, ICCIT 2022

作者： Jahangir, Raiyan Wasif-Ul-Islam, Md. Mohim, Nasif Shahriar Ashraf, Anika Khan, Nafiz Imtiaz Islam, Muhammad Nazrul Military Institute of Science and Technology Department of Computer Science and Engineering Dhaka1216 Bangladesh

ISBN: (纸本)9798350346022

the visually impaired people have been previously brought into the sphere of learning and education using various assistive technology, which has the latent to improve. these technologies have primarily relied on haptic feedback. Similarly, these technologies or approaches require the assistance of sighted teachers or various costly tools. Moreover, these existing systems are typically restricted to teaching the alphabet or strokes of a single language. To address these research gaps, a system is developed that teaches visually impaired people to learn the writing of the alphabet. In the proposed system, the visually impaired learners will be guided by a voice-over from a computer to write alphabets on a graphics pad using a stylus. Finally, the written alphabet can be checked through an image-processing technique to measure its accuracy. the voice-over guide constantly monitors the strokes being made by the learner, and if the learner gives any wrong strokes or move out of the guided way when writing the pad, the system provides alert and instructions accordingly. the system also very successfully informed the visually impaired learners about their learning progress or accuracy of a particular alphabet and suggested improvement, if required. © 2022 IEEE.

关键词： Image processing

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Fuzzy Model for the Analysis of Corporate Degradation in Crisis Conditions 25

Fuzzy Model for the Analysis of Corporate Degradation in Cri...

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25th International conference on Soft Computing and Measurements, SCM 2022

作者： Nedosekin, Alexey O. Abdoulaeva, Zinaida I. Kurbanbaeva, Dinara F. Karpenko, Nadezhda A. LLC c-Finance Russia St. Petersburg Russia North-Western State Medical University Named after I. I. Mechnikov Department of Medical Informatics and Physics St. Petersburg Russia St. Petersburg State University of Film and Television Department of Computer Graphics and Design St. Petersburg Russia

ISBN: (数字)9781665496698

ISBN: (纸本)9781665496698

the paper presents a fuzzy model of corporate degradation, with the allocation of three sign levels of degradation. Each level of corporate degradation is represented by its quantitative and qualitative linguistic assessment. the following factors are used during the analysis: quick reinvestment ratio (QRIC), economic stability index (RI), level of equity of the organization. As a result statistical data are presented on the levels of corporate degradation within a group of 86 world largest industrial enterprises. Conclusion. It is necessary to learn how to link levels of corporate degradation with implicit factors of corporate culture (for example, presented. © 2022 IEEE.

关键词： Investments

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Latency and Bandwidth Microbenchmarks of Six US Department of Energy Systems in the Top500 25

Latency and Bandwidth Microbenchmarks of Six US Department o...

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25th IEEE International conference on Cluster Computing (CLUSTER)

作者： Pearson, Carl Siefert, Christopher M. Olivier, Stephen L. Prokopenko, Andrey Fuller, Timothy J. Hu, Jonathan J. Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (纸本)9798350370621

Developers of portable high-performance computing applications are often concerned with basic performance properties across a variety of systems. Although supercomputing systems are comprehensively benchmarked during their acceptance testing process, results are not publicly disseminated and comparisons are typically restricted to immediate predecessor systems. this work presents selected single-node microbenchmarks of archetypal United States Department of Energy computers present in the June 2023 Top 500 list. these systems feature Intel or AMD CPUs, including Xeon Phi, and AMD or Nvidia GPUs, and provide a reasonable reference for what users can expect from these systems.

关键词： graphics processors computer performance High performance computing Software performance

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Lowering the Power Consumption of Healthcare Centers in Bangladesh using Low-Power Consuming Computing Devices 25

Lowering the Power Consumption of Healthcare Centers in Bang...

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25th International conference on computer and Information Technology, ICCIT 2022

作者： Chowdhury, Maksudul Haque Shuvro Mistry, Sumit Shamaem, Syeda Nawar Numan, Orpa Tuhin, Rashedul Amin East West University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346022

Bangladesh's hospital receptions and wards use high-specification computers to do petty work such as patient information management, providing service information, billing and others. It is entirely unnecessary as the work performed by these computers can be done by any other low-power computing devices like thin clients or other small single-board computers. Based on this situation, the problem was identified, which was to evaluate the reduction of power consumption possible by using Low-power computing devices instead of traditional desktop computers in hospital receptions, pathology, and hospital wards. Other research studies also did a similar kind of work comparing power consumption between regular and single-board computers. Data were collected from several hospitals after visiting and observing the computer usage and hardware information used there. Alongside, the power consumption was also collected. the power consumed by a similar single-board computer, a Raspberry Pi-based system that can replace the hospital's computer system infrastructure, was also compared. It was found that a Raspberry Pi-based system can perform the same tasks consuming 4.2 times less energy than the current system. Finally, as future work, we can expand our study to other sectors like banks and offices where the existing system can be replaced with a Low-power Computing device-based system. Also, special software can be made for Raspberry Pi to optimize energy consumption further. © 2022 IEEE.

关键词： graphics processing unit

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Medical Image Interpretation with Large Multimodal Models 25

Medical Image Interpretation with Large Multimodal Models

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25th Working Notes of the conference and Labs of the Evaluation Forum, CLEF 2024

作者： Hoque, Mahmudul Hasan, Md Rakibul Emon, Md Ismail Siddiqi Khalifa, Fahmi Rahman, Md Mahmudur Computer Science Department Morgan State University 1700 East Cold Spring Lane BaltimoreMD21251 United States Electrical and Computer Engineering Department School of Engineering Morgan State University BaltimoreMD21251 United States

this working note documents the participation of CS_Morgan in the ImageCLEFmedical 2024 Caption subtasks, focusing on Caption Prediction and Concept Detection challenges. the primary objectives included training, validating, and testing multimodal Artificial Intelligence (AI) models intended to automate the process of generating captions and identifying multi-concepts of radiology images. the dataset used is a subset of the Radiology Objects in COntext version 2 (ROCOv2) dataset and contains image-caption pairs and corresponding Unified Medical Language System (UMLS) concepts. To address the caption prediction challenge, different variants of the Large Language and Vision Assistant (LLaVA) models were experimented with, tailoring them for the medical domain. Additionally, a lightweight Large Multimodal Model (LMM), and MoonDream2, a small Vision Language Model (VLM), were explored. the former is the instruct variant of the Image-aware Decoder Enhanced à la Flamingo with Interleaved Cross-attentionS (IDEFICS) 9B obtained through quantization. Besides LMMs, conventional encoder-decoder models like Vision Generative Pre-trained Transformer 2 (visionGPT2) and Convolutional Neural Network-Transformer (CNN-Transformer) architectures were considered. Consequently, this enabled 10 submissions for the caption prediction task, with the first submission of LLaVA 1.6 on the Mistral 7B weights securing the 2nd position among the participants. this model was adapted using 40.1M parameters and achieved the best performance on the test data across the performance metrics of BERTScore (0.628059), ROUGE (0.250801), BLEU-1 (0.209298), BLEURT (0.317385), METEOR (0.092682), CIDEr (0.245029), and RefCLIPScore (0.815534). For the concept detection task, our single submission based on the ConvMixer architecture-a hybrid approach leveraging CNN and Transformer advantages-ranked 9th with an F1-score of 0.107645. Overall, the evaluations on the test data for the caption prediction task submis

关键词： Radiology

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Efficient Computing for Reduced Density Matrix on GPUs 25

Efficient Computing for Reduced Density Matrix on GPUs

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25th IEEE International conferences on High Performance Computing and Communications, 9th International conference on Data Science and Systems, 21st IEEE International conference on Smart City and 9th IEEE International conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Liang, Wenhao Jin, Runfeng Tian, Yingqi Ma, Yingjin Jin, Zhong Computer Network Information Center Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Chemistry and Chemical Engineering Nanjing University Nanjing China

ISBN: (纸本)9798350330014

the reduced density matrix (RDM) plays an important role in quantum physics. With the RDM, we can accurately describe the energy of the quantum system. However, solving the RDM is a computationally intensive task where matrix multiplication accounts for more than 95% of the computation time, and exponential complexity, large memory consumption, and tensor sparsity make it challenging to achieve efficient computation. this paper proposes an efficient, scalable and multi-GPU solver for computing the RDM. the complexity of computing RDM is reduced to polynomial by using a tensor network approach in the form of matrix product state (MPS). the sparsity blocks are composed of contiguous memory locations using the list algorithm. the precomputation approach uses a small memory overhead to replace some redundant computations. Furthermore, the sparsity blocks are computed on the GPU using variable-size batch general matrix multiplication (GEMM). We benchmark the performance using a water molecule, and our results show that we achieve a 22.4 × speedup when using four MI50 GPUs compared to a 32-core CPU. Additionally, we demonstrate excellent strong scaling, achieving over 92% parallel efficiency when comparing the performance on 256 nodes versus 16 nodes. © 2023 IEEE.

关键词： graphics processing unit

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Towards Optimized Hydrological Forecast Prediction of WRF-Hydro on GPU 25

Towards Optimized Hydrological Forecast Prediction of WRF-Hy...

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作者： Liu, Hongrui Lei, Kelun Yang, Hailong Luan, Zhongzhi Qian, Depei School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9798350330014

Hydrological models are designed to simulate and predict the dynamic cycling of surface and groundwater. these models represent simplifications of complex hydrological pro-cesses and play an integral role in hydrological research and real-world applications. the WRF Hydro model is widely used due to its multi-scale capabilities for land-atmosphere modeling. Recent studies have focused on enhancing the performance of different modules in WRF through GPU parallel optimization techniques. However, WRF - Hydro has not been able to utilize the GPU for computations which leads to lower computational efficiency when simulating hydrological calculations over large regions for extended periods. In this paper, we first analyze the computational and communication bottlenecks in WRF Hydro. We then propose several methods for performance optimization accordingly. To address the computational bottleneck, we develop efficient GPU-based overland routing and channel routing, eliminating redundant calculations. Additionally, we adopt an improved block partitioning strategy to enhance memory access efficiency on the GPU. To tackle the communicational bottleneck, we adopt a packetized communication strategy to reduce the number of communication operation calls in channel routing and simplify the preprocessing operations for communication. Meanwhile, for overland routing, we employ multi-stream to minimize redundant synchronization operations and overlap communication with computation to reduce communication overhead. the evaluation results demonstrate that WRF -Hydro can achieve significant speedups in several simulation cases after applying our proposed optimizations, resulting in a maximum speedup of 6.67 ×. © 2023 IEEE.

关键词： graphics processing unit

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