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

7,392 篇 会议
347 篇 期刊文献
57 册 图书
17 篇 学位论文

馆藏范围

7,813 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,439 篇 工学
- 3,414 篇 计算机科学与技术...
- 1,714 篇 软件工程
- 1,072 篇 电气工程
- 711 篇 信息与通信工程
- 342 篇 控制科学与工程
- 338 篇 电子科学与技术（可...
- 302 篇 光学工程
- 233 篇 机械工程
- 224 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...
- 50 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...
1,594 篇 理学
- 779 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
- 79 篇 化学
556 篇 医学
- 456 篇 临床医学
- 103 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

868 篇 parallel process...
693 篇 image processing
325 篇 image segmentati...
297 篇 concurrent compu...
273 篇 distributed comp...
259 篇 computational mo...
252 篇 computer archite...
250 篇 feature extracti...
215 篇 image reconstruc...
194 篇 image edge detec...
186 篇 image coding
177 篇 graphics process...
170 篇 iterative method...
166 篇 hardware
165 篇 algorithm design...
164 篇 neural networks
159 篇 computer science
159 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
27 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

7,694 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 7813 条记录，以下是691-700 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：

Window-based parallel operator execution with in-network computing 22

Window-based parallel operator execution with in-network com...

引用

16th ACM International conference on distributed and Event-Based Systems, DEBS 2022

作者： Boughzala, Bochra Gärtner, Christoph Koldehoffe, Boris University of Groningen Groningen Netherlands Technical University of Darmstadt Darmstadt Germany

ISBN: (纸本)9781450393089

Data parallel processing is a key concept to increase the scalability and elasticity in event streaming systems. Often data parallelism is accomplished in a splitter-merger architecture where the splitter divides incoming streams into partitions and forwards them to parallel operator instances. The splitter performance is a limiting factor to the system throughput and the parallelization degree. This work studies how to leverage novel methods of in-network computing to accelerate the splitter functionality by implementing it as an in-network function. While dedicated hardware for in-network computing has a high potential to enhance the splitter performance, in-network programming models like the P4 language are also highly limited in their expressiveness to support corresponding parallelization models. We propose P4 Splitter Switch (P4SS) which supports overlapping and non-overlapping count-based windows for multiple independent data streams and parallelizes them to a dynamically configurable number of operator instances. We validate in the context of a prototypical implementation our splitting strategy and its scalability in terms of switch resource consumption. © 2022 Owner/Author.

关键词： Scalability

来源：评论

学校读者我要写书评

暂无评论

A Look at Performance and Scalability of the GPU Accelerated Sparse Linear System Solver Spliss 29th

A Look at Performance and Scalability of the GPU Accelerated...

引用

29th International conference on parallel and distributed Computing (Euro-Par)

作者： Mohnke, Jasmin Wagner, Michael German Aerosp Ctr DLR Inst Software Methods Prod Virtualizat Dresden Germany

ISBN: (纸本)9783031396977;9783031396984

A significant part in computational fluid dynamics (CFD) simulations is the solving of large sparse systems of linear equations resulting from implicit time integration of the Reynolds-averaged Navier-Stokes (RANS) equations. The sparse linear system solver Spliss aims to provide a linear solver library that, on the one hand, is tailored to these requirements of CFD applications but, on the other hand, independent of the particular CFD solver. Spliss allows leveraging a range of available HPC technologies such as hybrid CPU parallelization and the possibility to offload the computationally intensive linear solver to GPU accelerators, while at the same time hiding this complexity from the CFD solver. This work highlights the steps taken to establish multi-GPU capabilities for the Spliss solver allowing for efficient and scalable usage of large GPU systems. In addition, this work evaluates performance and scalability on CPU and GPU systems using a representative CODA test case as an example. CODA is the CFD software being developed as part of a collaboration between the French Aerospace Lab ONERA, the German Aerospace Center (DLR), Airbus, and their European research partners. CODA is jointly owned by ONERA, DLR and Airbus. The evaluation examines and compares performance and scalability in a strong scaling approach on Nvidia A100 GPUs and the AMD Rome architecture.

关键词： sparse linear solver computational fluid dynamics CFD solver high performance computing heterogeneous computing GPU

来源：评论

学校读者我要写书评

暂无评论

Research on Data Quality Management methods and Technologies

Research on Data Quality Management Methods and Technologies

引用

image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： Xuemin Wang Xinchi Li Xiaoqing Xia Research Institute of China Telecom Corporation Limited Beijing China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

With the rapid development of information technology, big data has become an important strategic resource for enterprises. However, with the increase in data volume, data quality issues are becoming increasingly prominent. Low data quality may lead to enterprises being unable to make accurate decisions, and even bring huge economic losses. This article first discusses the definition of data quality and the dimensions of data quality measurement, and then focuses on the measurement methods and architecture of data quality. It mainly summarizes the data quality comparison mode, technical implementation deployment, and proposes a distributed data quality audit architecture. Finally, it provides the steps and common software implementations for data quality management within the enterprise. In summary, this article aims to explore the significance, solutions, and implementation methods of data quality management, providing an effective theoretical basis for improving the data quality for enterprises.

关键词： Economics Accuracy Data integrity Large language models image processing Computer architecture Software Security Information technology Faces

来源：评论

学校读者我要写书评

暂无评论

parallel Algorithms Assessment Usage of image’s Segmentation Quality in Medicine 6

Parallel Algorithms Assessment Usage of Image’s Segmentatio...

引用

6th International conference on Computational Linguistics and Intelligent Systems, COLINS 2022 - Volume I: Main

作者： Mochurad, Lesia Lema, Halyna Vilhutska, Roksolana Lviv Polytechnic National University 12 Bandera street Lviv79013 Ukraine

There is an increase in medicine data quantity and image resolution requirements due to the modern medicine development, which leads to the necessity of strong computing resources and huge computer memory amount during the appropriate tasks’ modeling. Semantic segmentation in medicine implements assessment functions in diagnostics. However, there is a human factor that can lead to a great number of mistakes, it is critically important to do everything to minimize and accelerate the diagnostic process which will positively affect the field that is connected to the life and health risks. A parallel algorithm is a way of minimizing these problems and boosting the total processing of medical data. That is why the topical subject of work efficiency determination of parallel algorithms methods of biomedical images’ segmentation is being investigated in this work. In particular, we investigated methods such as the Vinegar Method, Sobel’s filter, and Canny edge detector. parallel computing technology CUDA has been chosen. An information system, which allows performing semantic image segmentation on the proposed parallel algorithm, was developed. The Sorensen index for semantic segmentation is about 0.45 and the acceleration of algorithms in some cases exceeds 10 times. Finished decision analysis, research of the subject area and scientific works related to this topic, as well as testing of the software product and identification of advantages and disadvantages in it are important except for this system projection. © 2022 Copyright for this paper by its authors.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Medical CT image Cutting and Diagnostic Discrimination Model based on Decision Tree and Deep Neural Network

Medical CT Image Cutting and Diagnostic Discrimination Model...

引用

distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International conference on

作者： Jiaxiang Li Xinru Fu School of Mathematics and Physics China University of Geosciences Wuhan China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Cancer, with a high mortality rate, remains one of the top priorities in medical research. Rectal cancer is a common and significant threat in the research studies of medical image processing. It is still a challenge to determine the accuracy of lymph node metastasis preoperatively using universally accepted methods with preoperative CT images. The report argues that technology that applies deep learning to precisely identify lymph node metastasis in patients suffering from rectal cancer when CT scan images are analyzed should be used. We present advanced strategies with deep learning algorithms for understanding and classifying CT images, which demonstrate a more improved probability of image classification over traditional methods. This paper will improve image classification accuracy over traditional methods and open a more promising way for preoperative-based assessment in the treatment of rectal cancer.

关键词： Deep learning image segmentation Computed tomography Feature extraction Data models Metastasis Decision trees Medical diagnostic imaging Lymph nodes image classification

来源：评论

学校读者我要写书评

暂无评论

A Time-Continuous Federated Learning Framework for Enabling Intelligent Applications Over Latency-Critical Aerial Networks

A Time-Continuous Federated Learning Framework for Enabling ...

引用

IEEE conference on Wireless Communications and Networking

作者： Swapnil Sadashiv Shinde Daniele Tarchi CNIT University of Bologna Research Unit Bologna Italy Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Bologna Italy

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

distributed Machine Learning (DML) methods are expected to play a crucial role in the forthcoming 6G era, with the goal of enabling ubiquitous connected intelligence. distributed intelligence enabled through distributed computing environments, 6G technology, and big data can be extremely supportive of achieving the goals of emerging intelligent IoT applications in the proximity of end users. With this in mind, we propose an advanced Federated Learning (FL) approach for efficiently enabling intelligent applications over latency-critical networks in Non-Terrestrial environments. In the proposed solution, the client and server nodes reduce idle time using a parallel processing approach with the help of a replica of the training model. Next, the proposed FL framework is tested in a Python environment to show its effectiveness with respect to the traditional FL approach.

关键词： Training Performance evaluation 6G mobile communication Costs Federated learning parallel processing Big Data

来源：评论

学校读者我要写书评

暂无评论

Research on Feature Extraction Algorithm of Graph Data Based on Graph Neural Network

Research on Feature Extraction Algorithm of Graph Data Based...

引用

Frontiers Technology of Information and Computer (ICFTIC), IEEE International conference on

作者： Shuang Qiu Hairong Hao Zhou Dong School of Information Engineering Eurasia University Xi'an China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

This paper proposes an optimization model that integrates Hadoop, Graph Convolutional Networks (GCN), and Ant Colony Optimization (ACO) to enhance GNN performance in large-scale networks. Hadoop is utilized for distributed storage and processing of large graph datasets, dividing them into subgraphs across multiple computing nodes. The MapReduce framework accelerates the training and inference of GCN through parallel computing. GCN is employed to extract node features by performing convolution on the graph's adjacency matrix. ACO is then applied for global hyperparameter tuning and network structure optimization. By exploring the parameter space, ACO identifies the optimal configuration for GCN. This model leverages Hadoop's distributed computing power, GCN's effective feature extraction, and ACO's optimization capabilities. Experimental results demonstrate improved efficiency and performance on large-scale network datasets compared to traditional methods.

关键词： Training Graph convolutional networks Convolution Optimization models Computational modeling parallel processing Feature extraction distributed computing Optimization Tuning

来源：评论

学校读者我要写书评

暂无评论

OpenMedIA: Open-Source Medical image Analysis Toolbox and Benchmark Under Heterogeneous AI Computing Platforms 5th

OpenMedIA: Open-Source Medical Image Analysis Toolbox and Be...

引用

5th Chinese conference on Pattern Recognition and Computer Vision (PRCV)

作者： Zhuang, Jia-Xin Huang, Xiansong Yang, Yang Chen, Jiancong Yu, Yue Gao, Wei Li, Ge Chen, Jie Zhang, Tong Peng Cheng Lab Shenzhen Peoples R China Harbin Inst Technol Shenzhen Sch Comp Sci & Technol Shenzhen Peoples R China Peking Univ Sch Elect & Comp Engn Beijing Peoples R China Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Peoples R China

ISBN: (纸本)9783031189067;9783031189074

In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms. Various medical image analysis methods, including 2D/3D medical image classification, segmentation, localisation, and detection, have been included in the toolbox with PyTorch and/or MindSpore implementations under heterogeneous NVIDIA and Huawei Ascend computing systems. To our best knowledge, OpenMedIA is the first opensource algorithm library providing compared PyTorch and MindSpore implementations and results on several benchmark datasets. The source codes and models are available at https://***/OpenMedIA.

关键词： Open systems

来源：评论

学校读者我要写书评

暂无评论

MAP image Recovery with Guarantees using Locally Convex Multi-Scale Energy (LC-MUSE) Model

MAP Image Recovery with Guarantees using Locally Convex Mult...

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Jyothi Rikhab Chand Mathews Jacob Department of Electrical and Computer Engineering University of Iowa IA USA Department of Electrical and Computer Engineering University of Virginia VA USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We propose a multi-scale deep energy model that is strongly convex in the local neighbourhood around the data manifold to represent its probability density, with application in inverse problems. In particular, we represent the negative log-prior as a multi-scale energy model parameterized by a Convolutional Neural Network (CNN). We restrict the gradient of the CNN to be locally monotone, which constrains the model as a Locally Convex Multi-Scale Energy (LC-MuSE). We use the learned energy model in image-based inverse problems, where the formulation offers several desirable properties: i) uniqueness of the solution, ii) convergence guarantees to a minimum of the inverse problem, and iii) robustness to input perturbations. In the context of parallel Magnetic Resonance (MR) image reconstruction, we show that the proposed method performs better than the state-of-the-art convex regularizers, while the performance is comparable to plug-and-play regularizers and end-to-end trained methods.

关键词： Manifolds Inverse problems Perturbation methods Magnetic resonance Signal processing Robustness Data models Convolutional neural networks Speech processing image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Low-resource Neural Machine Translation with Cross-modal Alignment

Low-resource Neural Machine Translation with Cross-modal Ali...

引用

2022 conference on Empirical methods in Natural Language processing, EMNLP 2022

作者： Yang, Zhe Fang, Qingkai Feng, Yang China University of Chinese Academy of Sciences Beijing China

How to achieve neural machine translation with limited parallel data? Existing techniques often rely on large-scale monolingual corpora, which is impractical for some low-resource languages. In this paper, we turn to connect several low-resource languages to a particular high-resource one by additional visual modality. Specifically, we propose a cross-modal contrastive learning method to learn a shared space for all languages, where both a coarse-grained sentence-level objective and a fine-grained token-level one are introduced. Experimental results and further analysis show that our method can effectively learn the cross-modal and cross-lingual alignment with a small amount of image-text pairs and achieves significant improvements over the text-only baseline under both zero-shot and few-shot scenarios. Our code could be found at https://***/ictnlp/LNMT-CA. © 2022 Association for Computational Linguistics.

关键词： image enhancement

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 << < 66 67 68 69 70 71 72 73 74 75 > >>

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：