检索结果-内蒙古大学图书馆

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Yusheng Liu Yingjie Zhao Meihuan Wang Yichao Hao Xiuying Wang Lisheng Wang Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China College of Medicine and Biological Information Engineering Northeastern University Shenyang China School of Computer Science The University of Sydney Sydney NSW Australia

In surgery-based renal cancer treatment, one of the most essential tasks is the three-dimensional (3D) kidney parsing on computed tomography angiography (CTA) images. In this paper, we propose an end-to-end convolutional neural network-based framework to segment multiple renal structures, including kidneys, kidney tumors, arteries, and veins from arterial-phase CT images. Our method consists of two collaborative modules: First, we propose an encoding-decoding network, named Multi-Branch Dilated Convolutional Network (MBD-Net), consisting of residual, hybrid dilated convolutional, and reduced-dimensional convolutional structures, which improves the feature extraction ability with relatively fewer network parameters. Given that renal tumors and cysts have confusing geometric structures, we also design the Cyst Discriminator to effectively distinguish tumors from cysts without labeling information via gray-scale curves and radiographic features. We have quantitatively evaluated our approach on a publicly available dataset from MICCAI 2022 Kidney Parsing for Renal Cancer Treatment Challenge (KiPA2022), with mean Dice similarity coefficient (DSC) as 96.18%, 90.99%, 88.66% and 80.35% for the kidneys, kidney tumors, arteries, and veins respectively, winning the stable and top performance in the *** relevance—The proposed CNN-Based framework can automatically segment 3D kidneys, renal tumors, arteries, and veins for kidney parsing techniques, benefiting surgery-based renal cancer treatment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Variational Quantum Linear Solver enhanced Quantum Support Vector Machine

arXiv

引用

arXiv 2023年

作者： Yi, Jianming Suresh, Kalyani Moghiseh, Ali Wehn, Norbert Image Processing Department Fraunhofer Institute for Industrial Mathematics ITWM Kaiserslautern67663 Germany Microelectronic Systems Design Research Group RPTU Kaiserslautern-Landau Kaiserslautern67633 Germany Leibniz Universität Hannover Appelstraße 2 Hannover30167 Germany

Quantum Support Vector Machines (QSVM) play a vital role in using quantum resources for supervised machine learning tasks, such as classification. However, current methods are strongly limited in terms of scalability on Noisy Intermediate Scale Quantum (NISQ) devices. In this work, we propose a novel approach called the Variational Quantum Linear Solver (VQLS) enhanced QSVM. This is built upon our idea of utilizing the variational quantum linear solver to solve system of linear equations of a least squares-SVM on a NISQ device. The implementation of our approach is evaluated by an extensive series of numerical experiments with the Iris dataset, which consists of three distinct iris plant species. Based on this, we explore the practicality and effectiveness of our algorithm by constructing a classifier capable of classification in a feature space ranging from one to seven dimensions. Furthermore, by strategically exploiting both classical and quantum computing for various subroutines of our algorithm, we effectively mitigate practical challenges associated with the implementation. These include significant improvement in the trainability of the variational ansatz and notable reductions in run-time for cost calculations. Based on the numerical experiments, our approach exhibits the capability of identifying a separating hyperplane in an 8-dimensional feature space. Moreover, it consistently demonstrated strong performance across various instances with the same dataset. © 2023, CC BY-SA.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Temporal and Spatial Perception: A Novel Perceptual Rate-Distortion Optimization Method for H.266/VVC Encoding

引用

IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Ai, Da Wang, Jiahao He, Ting Yuan, Hui Liu, Ying Ling, Nam Xi'an University of Posts and Telecommunications Center for Image and Information Processing School of Communications and Information Engineering Xi'an710121 China Shandong University School of Control Science and Engineering Jinan250061 China Shandong University Shenzhen-Research Institute Shenzhen518057 China Santa Clara University Department of Computer Science and Engineering Santa ClaraCA95053 United States

Introducing saliency information to mitigate perceptual redundancy and achieve superior compression represents a novel approach to the development of video compression. Existing saliency-based compression coding methods rely on the determination of saliency regions and focus too much on saliency regions while ignoring the perceptible distortion in non-saliency regions. We propose a spatiotemporal visual perceptual rate-distortion optimization (PRDO) algorithm for Versatile Video Coding (H.266/VVC) that is more in line with the human visual system (HVS). Firstly, we establish a linear weighted distortion model based on spatiotemporal and saliency features. The distortion model makes effective use of saliency features while considering image content in non-saliency regions that is still perceptible to the human eye, thereby achieving an overall visual effect that conforms to human subjective perception. Based on this distortion model, we propose a saliency adaptive quantization parameter (SAQP) selection method with a more flexible quantization parameter selection range, adaptively allocating the optimal coding unit quantization parameter according to the saliency regions of the image, ensuring a balanced bitrate allocation between saliency and non-saliency regions. The proposed method is implemented for the first time on the H.266/VVC coding standard, attaining an average bitrate saving of 19.9% across all test sequences and an average PSNR improvement of 2.65 dB in saliency regions compared to VTM16.0. The BD-EWPSNR of the proposed PRDO and SAQP method improves by 1.34 dB and 1.45 dB in the All-Intra and Lowdelay-P encoding modes, respectively. Additionally, the BD-Rate based on EWPSNR is reduced by 25.86% and 33.73%, respectively, with an overall compression coding time saving of 19.76%. The experimental results demonstrate that the proposed method can significantly reduce the bit rate and coding time while improving the subjective perceptive quality, providing a c

关键词： Signal distortion

来源：评论

学校读者我要写书评

暂无评论

A theoretical framework for the assessment of water fraction-dependent longitudinal decay rates and magnetisation transfer in membrane lipid phantoms

arXiv

引用

arXiv 2024年

作者： Neeb, Heiko Schyboll, Felix Shaharabani, Rona Mezer, Aviv A. Shtangel, Oshrat Department of Mathematics Computer Science and Technology University of Applied Sciences Koblenz RheinAhrCampus Remagen Germany Institute for Medical Engineering and Information Processing - MTI Mittelrhein University of Koblenz Germany Edmond and Lily Safra Center for Brain Sciences Hebrew University of Jerusalem Israel

Motivation Phantom systems consisting of liposome suspensions are widely employed to investigate quantitative MRI parameters mimicking cellular membranes. The proper physical understanding of the measurement results, however, requires proper models for liposomes and their interaction with the surrounding water molecules. Molecular dynamics (MD) simulations allow for investigating the basic lipid-water interaction and determining quantitative MR parameters such as R1 = 1/T1. Here, we present an MD-based approach for the theoretical prediction of R1, the dependence of R1 on water concentration and the magnetization exchange between lipids and interacting water layer in lipids and lipid mixtures. Moreover, a new parameter is introduced which quantitatively measures the amount of hydration water based on conventional spoiled gradient echo MR acquisitions. Methods Molecular dynamics simulations were performed to determine the native R1 rates in three lipids and their interacting water pools. Employing a three-pool exchange model between lipid, hydration water and free water, the hydration water fraction, fHW, as a new parameter as well as the magnetization transfer rate between hydration water and lipids, kHW,L, were quantitatively determined, from which the water concentration dependence of R1 was predicted for all liposome systems investigated. Results Both fHW and kHW,L were determined quantitatively from spoiled gradient echo data by taking the MD-determined relaxation rates into account. Liposome systems behaved similarly, apart from PLPC which showed both lower hydration water fraction and lower exchange rate. The extracted parameters accurately predicted the measured water fraction-dependent R1 rates. Conclusion Hydration water fraction and magnetisation transfer between lipids and water can be determined by a combination of spoiled gradient echo acquisitions and MD-derived relaxation rates. The parameters enable a theoretical understanding of MR parameters in lip

关键词： Phantoms

来源：评论

学校读者我要写书评

暂无评论

A technical primer on the physical modeling of diffusion-encoded magnetic resonance experiments: A random process perspective

arXiv

引用

arXiv 2021年

作者： Haldar, Justin P. Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California

Diffusion-encoded magnetic resonance (MR) experiments can provide important insights into the microstructural characteristics of a variety of biological tissues and other fluid- or gas-filled porous media. The physics of diffusion encoding has been studied extensively over the span of many decades, and many excellent descriptions can be found in the literature - see, e.g., Refs. [1-5]. However, many of these descriptions spend relatively little time focusing on random process descriptions of the diffusion process, instead relying on different abstractions. In this primer, we describe diffusion-encoded MR experiments from a random process perspective. While the results we derive from this perspective are quite standard (and match the results obtained with other arguments), we expect that the alternative derivations may be insightful for some readers. This primer is intended for technical readers who have a graduate-level understanding of random processes. Readers are also expected to already have good familiarity with the basics of MR, and we anticipate that a signal processing perspective on MR [6] will be especially complementary to the random process perspectives presented herein. © 2021, CC BY-NC-ND.

关键词： Magnetic resonance

来源：评论

学校读者我要写书评

暂无评论

Raspberry Pi-Based Monitoring System for Grid-Connected PV Systems using Deep Learning Technique*

Raspberry Pi-Based Monitoring System for Grid-Connected PV S...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Zahra Yahyaoui Wajdi Saadaoui Mansour Hajji Majdi Mansouri Mohamed Nounou Kais Bouzrara Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Tunisia Department of Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The evolution of embedded systems has demonstrated their reliability as a solution for monitoring and controlling industrial systems, particularly in renewable energy conversion systems like photovoltaic (PV) energy. The increasing adoption of PV systems highlights the critical need for effective fault diagnosis to ensure their reliable operation. In this paper, we present a novel fault diagnosis approach utilizing Long Short-Term Memory (LSTM) networks optimized through Bayesian optimization techniques. Our methodology is implemented on a Raspberry Pi platform, demonstrating the feasibility of deploying sophisticated fault diagnosis algorithms in resource-constrained environments. Through extensive experiments, we demonstrate the effectiveness of our approach to accurately diagnose faults in grid-connected photovoltaic systems, thereby improving the reliability and efficiency of integrated environmental monitoring *** obtained results highlight the potential of combining advanced deep learning techniques with embedded systems to address complex diagnostic challenges, as demonstrated by achieving a 100% accuracy rate.

关键词： Fault diagnosis Deep learning Photovoltaic systems Embedded systems Accuracy Economic indicators Bayes methods Environmental monitoring Long short term memory Optimization

来源：评论

学校读者我要写书评

暂无评论

Exploring the Potential of Large Language Models for Red Teaming in Military Coalition Networks

Exploring the Potential of Large Language Models for Red Tea...

引用

MILCOM, Military Communications Conference

作者： Erik Adler Johannes F. Loevenich Linnet Moxon Tobias Hürten Florian Spelter Johannes Braun Yann Gourlet Thomas Lefeuvre Roberto Rigolin F. Lopes Secure Communications & Information (SIX) Thales Deutschland Ditzingen Germany Department of Computer Science Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Department of Mathematics/Computer Science University of Osnabrück Osnabrück Germany Institute for Natural Language Processing (IMS) University of Stuttgart Stuttgart Germany Department of Computer Science IV Rheinische Friedrich Wilhelms Universität Bonn Germany Department of Computer Science University of Stuttgart Stuttgart Germany École Supérieure d’Ingénieurs de Rennes (ESIR) University of Rennes Rennes France

ISBN: (数字)9798350374230

ISBN: (纸本)9798350374247

This paper reports on an ongoing investigation comparing the performance of large language models (LLMs) in generating penetration test scripts for realistic red agents. The goal is to develop human-level adversaries (red agents) in an automated cyber operations gym environment instrumented to train a team of blue agents. Our methodology defines five approaches for structuring the prompts used to generate Metasploit scripts to exploit vulnerabilities described in Common Vulnerabilities Exposures (CVEs). These approaches have been tested using three LLMs, namely GPT-4o, WhiteRabbitNeo, and Mistral-7b. GPT-4o is used as the baseline for our comparison study. The results suggest that GPT-4o outperforms the other LLMs in all experiments. However, the results also suggest that Mistral-7b can be fine-tuned to achieve acceptable performance while consuming much less computational and memory resources during execution due to a smaller number of parameters: 7 billion parameters for Mistral-7b versus 1.76 trillion for GPT-4o.

关键词： Training Performance evaluation Military computing Large language models Instruments Computational modeling Memory management Reinforcement learning Usability Testing

来源：评论

学校读者我要写书评

暂无评论

Isoform Function Prediction Based on Heterogeneous Graph Attention Networks

Isoform Function Prediction Based on Heterogeneous Graph Att...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Kuo Guo Yifan Li Hao Chen Hong-Bin Shen Yang Yang Department of Computer Science and Engineering Shanghai Jiao Tong University and Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Computational Biology Department School of Computer Science Carnegie Mellon University Pittsburgh PA USA

Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bioinformatics as it can provide valuable insights into the intricate mechanisms of gene regulation and biological processes. Conventionally, gene function labels are standardized in Gene Ontology (GO) terms. However, traditional methods for predicting isoform function are largely limited by the absence of isoform-specific labels, sparse annotations, and the vast number of GO terms. To address these issues, we propose HANIso, a deep learning-based method for isoform function prediction. HANIso leverages a pretrained protein language model to extract features from protein sequences. It also integrates heterogeneous information, such as isoform sequence features, GO annotations, and isoform interaction data, using a Heterogeneous Graph Attention Network (HAN). This allows the model to learn the importance of different sources of information and their semantic relationships through the attention mechanism. Our method can predict function labels at both the gene level and isoform level. We conduct experiments on two species datasets, and the results demonstrate that our method outperforms existing methods on both AUROC and AUPRC. HANIso has the potential to overcome the limitations of traditional methods and provide a more accurate and comprehensive understanding of isoform function.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Graph learning and augmentation based interpolation of signal strength for location-aware communications 28

Graph learning and augmentation based interpolation of signa...

引用

28th European Signal processing Conference, EUSIPCO 2020

作者： Chiu, Hong-Ming Fung, Carrson C. Ortega, Antonio Dept. of Electronics Engineering National Chiao Tung University Hsinchu Taiwan Institute of Electronics National Chiao Tung University Hsinchu Taiwan Signal and Image Processing Institute Department of Electrical and Computer Engineering University of Southern California Los Angeles United States

ISBN: (纸本)9789082797053

A graph learning and augmentation (GLA) technique is proposed herein to solve the received signal power interpolation problem, which is important for preemptive resource allocation in location-aware communications. A graph parameterization results in the proposed GLA interpolator having superior mean-squared error performance and lower computational complexity than the traditional Gaussian process method. Simulation results and analytical complexity analysis are used to prove the efficacy of the GLA interpolator. © 2021 European Signal processing Conference, EUSIPCO. All rights reserved.

关键词： Interpolation

来源：评论

学校读者我要写书评

暂无评论

Multi-frame and multi-scale conditional generative adversarial networks for efficient foreground extraction 4th

Multi-frame and multi-scale conditional generative adversari...

引用

4th International Conference on computer Vision and image processing, CVIP 2019

作者： Didwania, Himansu Ghatak, Subhankar Rup, Suvendu Image and Video Processing Lab Department of Computer Science and Engineering International Institute of Information Technology Bhubaneswar Bhubaneswar751003 India

ISBN: (纸本)9789811540172

Alongside autonomous submissions, foreground extraction is considered to be the foundation for various video content analysis technologies, like moving object tracking, video surveillance and video summarization. This paper proposes an efficient foreground extraction methodology based on conditional Generative Adversarial Network. The proposed generator, which is made up of two networks working in series- Foreground Extractor and Segmentation Network, maps the video frames to corresponding foreground masks. The discriminator aids the learning of generator by learning to differentiate between seemingly real and fake foreground maps. The method used a multi-scale approach in order to capture robust features across multiple scales of input using the Feature Extractor Network, which are then used by the successive Segmentation Network to produce the final foreground map. In addition, a multi-frame approach is also used to facilitate capturing of appropriate temporal features. The performance of the proposed model is evaluated on CDnet 2014 Dataset and outperforms existing methods. © Springer Nature Singapore Pte Ltd 2020.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：