检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

7,385 篇 会议
347 篇 期刊文献
28 册 图书
16 篇 学位论文

馆藏范围

7,776 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,437 篇 工学
- 3,413 篇 计算机科学与技术...
- 1,714 篇 软件工程
- 1,071 篇 电气工程
- 711 篇 信息与通信工程
- 342 篇 控制科学与工程
- 337 篇 电子科学与技术（可...
- 302 篇 光学工程
- 233 篇 机械工程
- 222 篇 生物医学工程（可授...
- 177 篇 仪器科学与技术
- 154 篇 生物工程
- 90 篇 测绘科学与技术
- 59 篇 化学工程与技术
- 56 篇 航空宇航科学与技...
- 49 篇 材料科学与工程（可...
- 47 篇 土木工程
- 41 篇 动力工程及工程热...
- 40 篇 力学（可授工学、理...
1,593 篇 理学
- 778 篇 物理学
- 686 篇 数学
- 181 篇 生物学
- 143 篇 统计学（可授理学、...
- 142 篇 系统科学
- 78 篇 化学
554 篇 医学
- 455 篇 临床医学
- 101 篇 特种医学
- 80 篇 基础医学(可授医学...
444 篇 管理学
- 287 篇 管理科学与工程(可...
- 175 篇 图书情报与档案管...
- 73 篇 工商管理
37 篇 法学
36 篇 农学
23 篇 经济学
20 篇 文学
17 篇 教育学
7 篇 艺术学
6 篇 军事学

主题

866 篇 parallel process...
693 篇 image processing
324 篇 image segmentati...
297 篇 concurrent compu...
276 篇 distributed comp...
259 篇 computational mo...
252 篇 computer archite...
252 篇 feature extracti...
216 篇 image reconstruc...
194 篇 image edge detec...
187 篇 image coding
177 篇 graphics process...
170 篇 iterative method...
167 篇 hardware
166 篇 algorithm design...
164 篇 neural networks
159 篇 computer science
158 篇 deep learning
142 篇 pixel
141 篇 graphics process...

机构

47 篇 national laborat...
25 篇 college of compu...
21 篇 natl univ def te...
20 篇 natl univ def te...
19 篇 science and tech...
14 篇 natl univ def te...
13 篇 school of comput...
12 篇 univ chinese aca...
11 篇 king saud univer...
11 篇 university of ch...
11 篇 natl univ def te...
10 篇 national univers...
9 篇 natl univ def te...
9 篇 institute of inf...
9 篇 national laborat...
8 篇 natl univ def te...
8 篇 department of co...
8 篇 national laborat...
8 篇 college of compu...
8 篇 school of comput...

作者

37 篇 dou yong
28 篇 luo zhigang
26 篇 yong dou
21 篇 zhang xiang
19 篇 zhigang luo
18 篇 li dongsheng
17 篇 naiyang guan
17 篇 qiao peng
15 篇 huang xuhui
15 篇 jie liu
14 篇 niu xin
13 篇 yijie wang
13 篇 lan long
13 篇 wang huaimin
12 篇 anon
11 篇 xiang zhang
11 篇 yang yang
11 篇 liu jie
11 篇 wang yijie
11 篇 pesquet jean-chr...

语言

7,657 篇 英文
63 篇 其他
49 篇 中文
7 篇 土耳其文
3 篇 俄文

检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

共 7776 条记录，以下是461-470 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

GPU-Accelerated FDTD Solver for Electromagnetic Differential Equations 24th

GPU-Accelerated FDTD Solver for Electromagnetic Differential...

引用

24th International conference on Computational Science (ICCS)

作者： HoseinyFarahabady, MohammadReza Zomaya, Albert Y. Univ Sydney Ctr Distributed & High Performance Comp Sch Comp Sci Sydney NSW Australia

ISBN: (纸本)9783031637537;9783031637513

Computational electromagnetics plays a crucial role across diverse domains, notably in fields such as antenna design and radar signature prediction, owing to the omnipresence of electromagnetic phenomena. Numerical methods have replaced traditional experimental approaches, expediting design iterations and scenario characterization. The emergence of GPU accelerators offers an efficient implementation of numerical methods that can significantly enhance the computational capabilities of partial differential equations (PDE) solvers with specific boundary-value conditions. This paper explores parallelization strategies for implementing a Finite-Difference Time-Domain (FDTD) solver on GPUs, leveraging shared memory and optimizing memory access patterns to achieve performance gains. One notable innovation presented in this research involves utilizing strategies such as exploiting temporal locality and avoiding misaligned global memory accesses to enhance data processing efficiency. Additionally, we break down the computation process into multiple kernels, each focusing on computing different electromagnetic (EM) field components, to enhance shared memory utilization and GPU cache efficiency. We implement crucial design optimizations to exploit GPU's parallel processing capabilities fully. These include maintaining consistent block sizes, analyzing optimal configurations for field-updating kernels, and optimizing memory access patterns for CUDA threads within warps. Our experimental analysis verifies the effectiveness of these strategies, resulting in improvements in both reducing execution time and enhancing the GPU's effective memory bandwidth. Throughput evaluation demonstrates performance gains, with our CUDA implementation achieving up to 17 times higher throughput than CPU-based methods. Speedup gains and throughput comparisons illustrate the scalability and efficiency of our approach, showcasing its potential for developing large-scale electromagnetic simulations on

关键词： Numerical Computational Electromagnetics GPU Accelerators Finite-Difference Time-Domain Solver Partial Differential Equations Geometric Discretization

来源：评论

学校读者我要写书评

暂无评论

Enhancing Deep Learning-based Depression Level Estimation Based on Multi-task Learning 24

Enhancing Deep Learning-based Depression Level Estimation Ba...

引用

7th International conference on Machine Learning and Machine Intelligence, MLMI 2024

作者： Ye, Qingxin Xie, Zhenming Sun, Hao Xin, Luyao Chen, Youwen Song, Jian Chen, Yen-Wei Provincial key Laboratory of Computational Science Huaqiao University Quanzhou China Intelligent Image Processing Lab Zhejiang University Hangzhou China Intelligent Image Processing Lab Ritsumeikan University Osaka Japan

ISBN: (纸本)9798400717833

In recent years, depression, as a serious mental illness, has received widespread attention from various sectors of society. How to identify depressive emotions in a timely manner and detect depression has become an urgent issue that needs to be addressed. Currently, many experts and scholars propose using deep learning methods to assess the level of depression. Compared to other deep learning models, Transformer models have parallel computing capabilities with their self-attention mechanism, enabling them to handle entire sequences and capture long-distance dependencies. After the success of Transformers in natural language processing, similar architectures have been introduced into the field of computer vision, promoting advancements in multi-modal research. However, how to integrate other information or tasks to improve assessment accuracy remains a challenge. In our team's preliminary work, we proposed a multi-modal adaptive fusion Transformer network for assessing depression levels. Inspired by multi-task learning, we introduced gender classification as a second auxiliary task alongside the main task of depression regression, forming a three-task learning framework including depression classification. This was done to enhance the model's performance. We validated the effectiveness of the proposed method by testing it on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge). The experimental results show that our proposed method achieved a Concordance Correlation Coefficient (CCC) of 0.60448, which is 1.688% higher than the accuracy of the dual-task learning method (CCC = 0.5876). © 2024 Copyright held by the owner/author(s).

关键词： Multi-task learning

来源：评论

学校读者我要写书评

暂无评论

MSTCNet: parallel Multi-Scale Network for Medical image Segmentation 23

MSTCNet: Parallel Multi-Scale Network for Medical Image Segm...

引用

2023 4th International conference on Control, Robotics and Intelligent System, CCRIS 2023

作者： Xiao, Hongzhao Tang, Jie Song, Hongjian Hu, Juncheng South China University of Technology Guangdong Guangzhou China Guilin Medical University Guangxi Guilin China

ISBN: (纸本)9798400708190

Transformer-like architectures, which are the model of choice in the field of natural language processing, have recently been adapted to computer vision (CV) fields and demonstrated remarkable effectiveness on various CV tasks. However, current transformer-based methods require large-scale datasets, which are usually unavailable in medical image analysis, thus resulting in adverse achievement. To this end, we propose a novel segmentation model, named MSTCNet, which constructs a parallel multi-scale transformer (MST) encoder in U-Net. In MST, we devise multi-scale patch partition and multi-scale mix attention to perform multi-scale long-range dependencies modeling. The U-Net encoder paralleled with MST alleviates the burden of large-scale datasets and extract local features supplementarily. We also propose Feature Fusion Head to narrow the gap between convolutional features and transformer features. Sufficient experiments demonstrate that our MSTCNet outperforms state-of-the-art methods on GlaS and ISIC18 datasets and is more suitable for medical image segmentation with small-scale datasets. © 2023 ACM.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Mask-Guided Transformer for Human-Object Interaction Detection

Mask-Guided Transformer for Human-Object Interaction Detecti...

引用

IEEE International conference on Visual Communications and image processing (VCIP)

作者： Ying, Daocheng Yang, Hua Sun, Jun Shanghai Jiao Tong Univ Shanghai Key Lab Digital Media Proc & Transmiss Inst Image Commun & Network Engn Shanghai Peoples R China Shanghai Jiao Tong Univ AI Inst MoE Key Lab Artificial Intelligence Shanghai Peoples R China

ISBN: (纸本)9781665475921

Human-object interaction (HOI) detection is a meaningful research topic on human activity understanding. Recent works have made significant progress by focusing on efficient triplet matching and leveraging image-wide features based on encoder-decoder architecture. However, the ability to gather relevant contextual information about human is limited and different sub-tasks in HOI detection are not differentiated by specific decoupling in previous methods. To this end, we propose a new transformer-based method for HOI detection, namely, Mask-Guided Transformer (MGT). Our model, which is composed of five parallel decoders with a shared encoder, not only emphasizes interactive regions by applying body features, but also disentangles the prediction of instance and interaction. We achieve a favorable result at 63.3 mAP on the well-known HOI detection dataset V-COCO.

关键词： Transformers Object detection Human and object interaction HOI detection

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Graph-Sequence Anomaly Detection for 5G Core Network Control Plane Traffic 29

Unsupervised Graph-Sequence Anomaly Detection for 5G Core Ne...

引用

29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Wang, Min Li, Peng Cheng, Zhang Liu, Wenmao Nie, Lei Bao, Haizhou Liu, Qin Zhang, Kai Wuhan University of Science and Technology School of Computer Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System China Nsfocus Technologies Group Co. Ltd China Wuhan University School of Cyber Science and Engineering China

ISBN: (纸本)9798350330717

5G Core network (5GC) employs a Service Based Architecture (SBA). This architecture decomposes the control plane into multiple independent Network Functions (NFs). NFs open interfaces to provide services to other NFs, which makes the control plane more susceptible to external malicious attacks. However, existing anomaly detection methods focus more on traffic statistics features and are difficult to apply to the 5GC control plane. In this paper, we proposed GSAD, a Graph-Sequence analysis-based Anomaly Detection method for 5GC control plane traffic. We model control plane traffic as a directed graph to depict topological and NF interaction information. Further, we use the normalizing flows with temporal dependencies to mine the sequential information in the traffic. GSAD combines the topological and sequential information to provide fine-grained detection. We evaluate our proposed framework on the 5GC testbed using Free5GC and UERANSIM in various scenarios. Experimental results demonstrate that our framework outperforms the baselines significantly in terms of detection performance. © 2023 IEEE.

关键词： 5G core network anomaly detection control plane graph neural network normalizing flows

来源：评论

学校读者我要写书评

暂无评论

distributed Training Based on Horizontal Scaling for Food image Classification

Distributed Training Based on Horizontal Scaling for Food Im...

引用

International conference on Embedded & distributed Systems (EDiS)

作者： Gasbaoui Mohammed el Amin Benkrama Soumia Bendjima Mostefa Abden Sofiane Kourtiche Ikram Mathematics and Computer Science Department Laboratory of TIT Tahri Mohammed University Bechar Algeria

ISBN: (数字)9798331519872

ISBN: (纸本)9798331519889

Deep learning models for food image classification rely on vast amounts of data to effectively recognize and differentiate between various food items. However, training these models on such extensive datasets presents significant computational challenges. Big data and distributed training are inherently complementary in addressing these challenges. Big data involves large volumes of information that traditional single-machine processing cannot handle efficiently. distributed training offers a solution by enabling machine learning models to scale across multiple machines or nodes, thereby more effectively processing and learning from extensive datasets. By partitioning tasks into smaller chunks processed in parallel, distributed training optimizes computational resources, ensuring efficient analysis of big data while maintaining fault tolerance and performance scalability. This paper explores various strategies for distributed training and communication between GPUs. We compare the performance and utilization of a single P100 GPU versus two T4 GPUs on the Food-11 dataset, focusing on accuracy and training time. Our results indicate that using two GPUs yields slightly better performance than a single GPU, reducing the training time by 125 seconds, decreasing the validation dataset loss by 0.02, and increasing the accuracy by 1%. The overall accuracy achieved is 92%, with a corresponding loss of 0.28.

关键词： Training Accuracy Computational modeling Scalability Graphics processing units Big Data parallel processing Computational efficiency Synchronization image classification

来源：评论

学校读者我要写书评

暂无评论

FuseME: distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation 22

FuseME: Distributed Matrix Computation Engine based on Cuboi...

引用

International conference on Management of Data (SIGMOD)

作者： Han, Donghyoung Lee, Jongwuk Kim, Min-Soo Korea Adv Inst Sci & Technol Daejeon South Korea Sungkyunkwan Univ Seoul South Korea

ISBN: (纸本)9781450392495

Operator fusion is essentially and widely used in a large number of matrix computation systems in science and industry. The existing distributed operator fusion methods focus on only either low communication cost with the risk of out of memory or large-scale processing with high communication cost. We propose a distributed elastic fused operator called Cuboid-based Fused Operator (CFO) that achieves both low communication cost and large-scale processing. We also propose a novel fusion plan generator called Cuboid-based Fusion plan Generator (CFG) that finds a fusion plan to fuse more operators including large-scale matrix multiplication. We implement a fast distributed matrix computation engine called FuseME by integrating both CFO and CFG seamlessly. FuseME outperforms the state-of-the-art systems including SystemDS by orders of magnitude.

关键词： distributed data-parallel system operator fusion matrix operators

来源：评论

学校读者我要写书评

暂无评论

A Multi-staining Digital Pathology image Registration Method Based on Global and Local Computing

A Multi-staining Digital Pathology Image Registration Method...

引用

ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Yi Ding Xin Zhang Cheng Lu School of Computer and Cyber Sciences Communication University of China Beijing China Department of Radiology Guangdong Provincial People’s Hospital Guangzhou China

ISBN: (数字)9798350391954

ISBN: (纸本)9798350391961

To accurately evaluate the patient’s condition, medical workers usually need to register multiple pathological images of the lesion site samples. Using computer technology to assist in registration work can effectively improve the efficiency of doctors analyzing pathological images. One of the most advanced methods currently is the Virtual Alignment of Pathology image Series method, which is a multi-staining digital pathology image registration method that combines global and local calculations. However, this method may encounter certain biases when processing images with significant angle differences. Through a detailed analysis of this method, this article proposes an improvement plan which optimizes the acquisition of non-rigid registration mask images, enabling the method to obtain mask images more reasonably and achieve better registration results for images with significant angle differences. This provides more accurate judgment basis and helps doctors diagnose and develop treatment plans more accurately.

关键词： Pathology Solid modeling image registration Accuracy Medical services Software Registers

来源：评论

学校读者我要写书评

暂无评论

Design of UAV image Transmission System Based on Region of Interest Coding 3

Design of UAV Image Transmission System Based on Region of I...

引用

3rd International conference on Information Science, parallel and distributed Systems, ISPDS 2022

作者： Li, Wenyue Meng, Lingchun Guangdong University of Foreign Studies Network and Information Center Guangzhou China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

With the rapid development of the power industry, the scale of our country's power grid continues to expand, and transmission lines spread all over the country. The stability of transmission lines is one of the important factors to ensure stable power supply. The working environment of power transmission equipment is relatively harsh. Compared with other industrial sectors, transmission line failures are more dangerous and require higher stability. In order to ensure the stable operation of the power system, it is necessary to conduct regular inspections on the transmission lines. With the development of UAV technology and image processing technology, UAV line inspection technology based on video processing has become the most popular way of inspection of transmission lines. As a new operation and maintenance method in the power industry, the UAV line inspection system not only reduces the work intensity of transmission line operation and maintenance personnel, but also improves the quality, benefit and efficiency of inspections. It will be the main focus of transmission line operation and maintenance management in the future. Aiming at the problems such as unclear inspection interface and inconspicuous target focus caused by limited bandwidth when UAV patrols the line, this paper proposes a UAV image transmission system based on region of interest (ROI) coding. The system can effectively improve the clear reading of the target, thereby improving the effect and quality of the line inspection without increasing the total bandwidth. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Multi-Modal Medical image Fusion Technique using Optimal Sub-band Tree Structuring and Principal Component Analysis

A Hybrid Multi-Modal Medical Image Fusion Technique using Op...

引用

International conference on parallel distributed and Grid Computing (PDGC)

作者： Shailesh Bhosekar Prabhishek Singh Deepak Garg School of Computer Science and Artificial Intelligence SR University Warangal Telangana India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

In image processing, "image fusion" is the amalgamation of attributes and requirements from many images into a singular, more comprehensive representation. Multi-modal medical image fusion is a significant category of image fusion. It entails the integration of medical images acquired from several modalities. This work utilizes computed tomography (CT) scans, Positron Emission Tomography (PET) and magnetic resonance imaging (MRI) as modalities. This study (M3IF-SBTS) aims to construct a multi modal medical image approach that combines Optimal Sub-band Tree Structuring (SBTS) and Principal Component Analysis (PCA) with MRI and CT images in a manner that maximizes the information content in the fused image. The SBTS is an advanced wavelet transform version of Discrete Wavelet Transform (DWT), where signal is filtered more times. The PCA provides dimensionality reduction and retains the relevant features. The wavelet coefficients are fused using PCA-based fusion method. This combination of SBTS and PCA provides superior results compared to using SBTS, DWT, or PCA as individual methods. This improves overall visual and parametric quality of fusion results than many compared methods.

关键词： Visualization Magnetic resonance imaging Computed tomography Information filters Discrete wavelet transforms Positron emission tomography image fusion Principal component analysis Biomedical imaging Wavelet coefficients

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 43 44 45 46 47 48 49 50 51 52 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：