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

528 篇 会议
17 篇 期刊文献
7 册 图书

馆藏范围

552 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

355 篇 工学
- 283 篇 计算机科学与技术...
- 155 篇 软件工程
- 74 篇 电气工程
- 37 篇 信息与通信工程
- 20 篇 控制科学与工程
- 19 篇 光学工程
- 19 篇 生物医学工程（可授...
- 15 篇 电子科学与技术（可...
- 11 篇 仪器科学与技术
- 10 篇 机械工程
- 9 篇 生物工程
- 5 篇 测绘科学与技术
- 4 篇 建筑学
- 4 篇 土木工程
- 4 篇 化学工程与技术
- 3 篇 安全科学与工程
- 2 篇 力学（可授工学、理...
125 篇 理学
- 82 篇 物理学
- 40 篇 数学
- 13 篇 生物学
- 8 篇 统计学（可授理学、...
- 4 篇 化学
- 3 篇 系统科学
32 篇 医学
- 26 篇 临床医学
- 7 篇 特种医学
- 5 篇 基础医学(可授医学...
- 3 篇 药学(可授医学、理...
26 篇 管理学
- 21 篇 管理科学与工程(可...
- 6 篇 图书情报与档案管...
- 5 篇 工商管理
1 篇 农学

主题

53 篇 image processing
41 篇 parallel process...
26 篇 feature extracti...
25 篇 image segmentati...
23 篇 deep learning
23 篇 computer vision
21 篇 image edge detec...
20 篇 training
19 篇 image reconstruc...
17 篇 image analysis
16 篇 computer archite...
15 篇 neural networks
15 篇 computational mo...
14 篇 image color anal...
13 篇 distributed comp...
13 篇 accuracy
12 篇 image enhancemen...
12 篇 graphics process...
12 篇 parallel computi...
11 篇 algorithm design...

机构

7 篇 natl univ def te...
5 篇 national laborat...
4 篇 college of compu...
3 篇 hong kong polyte...
3 篇 univ carlos iii ...
3 篇 cnr inst biomed ...
3 篇 natl univ def te...
3 篇 sensetime res pe...
3 篇 cnr inst appl ma...
3 篇 natl univ def te...
2 篇 nanjing audit un...
2 篇 college of compu...
2 篇 school of comput...
2 篇 uni. of pisa
2 篇 univ sydney sch ...
2 篇 tsinghua univ ts...
2 篇 department of in...
2 篇 school of comput...
2 篇 univ aegean dept...
2 篇 lsi laboratory u...

作者

11 篇 dou yong
8 篇 zhigang luo
8 篇 naiyang guan
8 篇 qiao peng
8 篇 carretero jesus
6 篇 yong dou
5 篇 xiang zhang
5 篇 shi hc
5 篇 xu kele
5 篇 dacheng tao
5 篇 li hz
3 篇 ercan mf
3 篇 luo zhigang
3 篇 milanesi luciano
3 篇 garcia-blas javi...
3 篇 peng qiao
3 篇 li dongsheng
3 篇 abella monica
3 篇 xuhui huang
3 篇 huang xuhui

语言

547 篇 英文
4 篇 其他
1 篇 中文

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

共 552 条记录，以下是1-10 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：

Self-supervised Adversarial Hashing for Large-scale image Retrieval 30

Self-supervised Adversarial Hashing for Large-scale Image Re...

引用

30th IEEE International conference on parallel and distributed Systems, ICPADS 2024

作者： Cao, Yuan Xu, Xue Liu, Junwei Chen, Xiangru Ocean University of China School of Computer Science and Technology Qingdao China

ISBN: (纸本)9798331515966

Hashing has been widely used in large-scale image retrieval due to its high storage and search efficiency. Unsupervised learning saves a significant amount of labor costs compared to supervised learning. Existing unsupervised methods mostly convert unsupervised problems into supervised problems by reconstructing semantic information. In this paper, we propose a novel Self-supervised Adversarial Hashing (SAH) method which utilizes unsupervised semantic reconstruction methods along with self-supervised generative adversarial and contrastive learning methods to improve the model's accuracy and robustness. In addition, we propose a novel method for semantic relationship reconstruction, taking into account the similarity between different categories. Based on this, we have designed a multi-joint loss to further achieve reasonable intra-class aggregation and inter-class differentiation. The experimental results show that the proposed method outperforms state-of-the-art hashing methods for large-scale image retrieval. © 2024 IEEE.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

image denoising based on Swin Transformer Residual Conv U-Net 27

Image denoising based on Swin Transformer Residual Conv U-Ne...

引用

27th IEEE/ACIS International conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD)

作者： Gan, Yong Zhou, Shaohui Chen, Haonan Wang, Yuefeng Zhengzhou Univ Technol Zhengzhou Peoples R China Zhengzhou Univ Light Ind Coll Comp Sci & Technol Zhengzhou Peoples R China

ISBN: (纸本)9798350391961;9798350391954

In the field of computer vision, image denoising remains a fundamental and challenging problem, playing a crucial role in the preprocessing of various image processing tasks. The introduction of Convolutional Neural Networks (CNNs) into the image denoising domain has yielded significant improvements across different levels of visual tasks. In recent years, models based on the Swin Transformer have also been applied to the image denoising field, demonstrating superior denoising performance that surpasses CNN-based methods, thus becoming advanced techniques in current image denoising research. This paper proposes a Swin-Conv module that combines the local modeling capabilities of residual convolutional layers with the non-local modeling capabilities of the Swin Transformer and integrates this module into the UNet architecture for image denoising. For the dataset used in the model training process, data augmentation techniques were employed to randomly enhance the dataset, thereby improving overall robustness. The results indicate that the proposed Swin Transformer Residual Conv U-Net model shows improvement over current advanced networks, achieving PSNR and SSIM values of 36.09 and 0.963 at sigma = 15, 33.87 and 0.915 at sigma = 25, and 28.96 and 0.810 at sigma = 50.

关键词： image Denoising Deep Learning Transformer Convolutional Neural Networks U-Net

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 27

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

引用

27th IEEE/ACIS International conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD)

作者： Ding, Yi Zhang, Xin Lu, Cheng Commun Univ China Sch Comp & Cyber Sci Beijing Peoples R China Guangdong Prov Peoples Hosp Dept Radiol Guangzhou Peoples R China

ISBN: (纸本)9798350391961;9798350391954

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： digital pathological images global rigid registration local non-rigid registration feature point detection

来源：评论

学校读者我要写书评

暂无评论

imageMap: Enabling Efficient Mapping from image processing DSL to CGRA 30th

ImageMap: Enabling Efficient Mapping from Image Processing D...

引用

30th European conference on parallel and distributed processing (Euro-Par)

作者： Shi, Bizhao Dai, Tuo Zou, Sunan Wei, Xinming Luo, Guojie Peking Univ Sch Comp Sci Beijing Peoples R China Peking Univ Ctr Energy Efficient Comp & Applicat Beijing Peoples R China

ISBN: (纸本)9783031695766;9783031695773

image processing has broad application scenarios and fast-developing algorithms, requiring hardware platforms with both high energy efficiency and flexible programmability. Coarse-grained Reconfigurable Arrays (CGRAs) show great potential with their regular parallel architectures and word-level spatio-temporal reconfigurability. However, the mapping of image processing applications on CGRAs faces two main challenges: 1) low-level CGRA programming with multiple constraints brings difficulties for developers;2) the gaps between coarse-grained image pipelines and the fine-grained pipelined loops executed on CGRA generate a huge program transformation space. In order to tackle these challenges, we propose imageMap, an efficient mapping framework from Halide, an image processing DSL, to CGRAs. Firstly, we propose multi-level partitioning with the extended Halide scheduling primitives to decompose the complex applications systematically. Secondly, we propose a hierarchical program exploration algorithm specialized for CGRAs with the consideration of partitioning and CGRA performance modeling. Thirdly, we build an automatic compilation framework with several compilation optimization techniques to improve the mapping quality. In the experimental evaluations, imageMap performs better than existing work across multiple CGRA architectures and common image processing applications.

关键词： image processing Coarse-grained Reconfigurable Array CGRA Mapping

来源：评论

学校读者我要写书评

暂无评论

ER-SFM: Efficient and Robust Cluster-Based Structure from Motion 7th

ER-SFM: Efficient and Robust Cluster-Based Structure from Mo...

引用

7th Chinese conference on Pattern Recognition and Computer Vision

作者： Ye, Zongxin Li, Wenyu Liu, Sidun Qiao, Peng Dou, Yong Natl Univ Def Technol Coll Comp Natl Key Lab Parallel & Distributed Comp Changsha Peoples R China

ISBN: (纸本)9789819785070;9789819785087

Structure from Motion (SfM) is a fundamental computer vision technique that recovers scene structure and camera motion from multi-view images. When facing large-scale scenarios, cluster-based methods are commonly employed to improve reconstruction efficiency. However, these methods currently face challenges regarding their limited robustness, redundant computation, and drift. To address these issues, we propose a unified pipeline called ER-SfM, which enhances the three key aspects of cluster-based SfM: image clustering, local reconstruction, and merging. In terms of image clustering, we propose a three-stage image clustering method to ensure adequate and reliable connections between clusters. In the local reconstruction stage, we expedite the reconstruction process by eliminating duplicate point cloud computation. In the final merging stage, we introduce a global merging algorithm without scale ambiguity to address the drift problem. Extensive experimental results demonstrate the superior performance of our method in terms of both robustness and efficiency compared to state-of-the-art methods.

关键词： parallel structure from motion 3D Reconstruction image clustering Global averaging

来源：评论

学校读者我要写书评

暂无评论

PriCE: Privacy-Preserving and Cost-Effective Scheduling for parallelizing the Large Medical image processing Workflow over Hybrid Clouds 30th

PriCE: Privacy-Preserving and Cost-Effective Scheduling for ...

引用

30th European conference on parallel and distributed processing (Euro-Par)

作者： Wang, Yuandou Kanwal, Neel Engan, Kjersti Rong, Chunming Grosso, Paola Zhao, Zhiming Univ Amsterdam Multiscale Networked Syst Amsterdam Netherlands Univ Stavanger Dept Elect Engn & Comp Sci Stavanger Norway

ISBN: (纸本)9783031695766;9783031695773

Running deep neural networks for large medical images is a resource-hungry and time-consuming task with centralized computing. Outsourcing such medical image processing tasks to hybrid clouds has benefits, such as a significant reduction of execution time and monetary cost. However, due to privacy concerns, it is still challenging to process sensitive medical images over clouds, which would hinder their deployment in many real-world applications. To overcome this, we first formulate the overall optimization objectives of the privacy-preserving distributed system model, i.e., minimizing the amount of information about the private data learned by the adversaries throughout the process, reducing the maximum execution time and cost under the user budget constraint. We propose a novel privacy-preserving and cost-effective method called PriCE to solve this multi-objective optimization problem. We performed extensive simulation experiments for artifact detection tasks on medical images using an ensemble of five deep convolutional neural network inferences as the workflow task. Experimental results show that PriCE successfully splits a wide range of input gigapixel medical images with graph-coloring-based strategies, yielding desired output utility and lowering the privacy risk, makespan, and monetary cost under user's budget.

关键词： Privacy Cost-effectiveness Hybrid Clouds Medical image splitting Multi-Objective Optimization Scheduling

来源：评论

学校读者我要写书评

暂无评论

FERI: Feature Enhancement and Relational Interaction for image-text Matching 30

FERI: Feature Enhancement and Relational Interaction for Ima...

引用

30th IEEE International conference on parallel and distributed Systems, ICPADS 2024

作者： Zhang, Yu Zhang, Jianqiang Song, Gongpeng Lu, Qin Zhao, Shuo Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (纸本)9798331515966

image-text matching is an important problem at the intersection of computer vision and natural language processing. It aims to establish the semantic link between image and text to achieve high-quality semantic alignment between the two modalities. However, the existing methods have the problem that the meaning expressed in the image or the complex narrative in the text cannot be fully understood due to insufficient feature extraction. Moreover, due to the essential modal differences between images and texts, how to effectively and accurately align the semantic contents in images and texts has become the key of research. In order to solve the above problems, this paper proposes a method based on feature enhancement and relationship interaction. When processing images, the proposed method fuses labeled features, region features and location features to represent images. When processing text, a combination of Bi-GRU and self-attention mechanism is used to represent the text. In order to further align the semantic content in images and texts accurately, this paper improves two relational interaction mechanisms by identifying connection relationships and learning association relationships. Thus, the relation enhanced embedding is obtained. Finally, it calculated the similarity of the enhanced embedding to judge the matching degree of the image and text. Extensive experiments on the public datasets Flickr30K and MSCOCO demonstrate the effectiveness of our method. © 2024 IEEE.

关键词： cross-modal retrieval feature enhancement image-text matching relationship interaction

来源：评论

学校读者我要写书评

暂无评论

Robustness and Accuracy in Pipelined Bi-conjugate Gradient Stabilized methods 24th

Robustness and Accuracy in Pipelined Bi-conjugate Gradient S...

引用

24th International conference on Computational Science (ICCS)

作者： Havdiak, Mykhailo Aliaga, Jose, I Iakymchuk, Roman Ivan Franko Natl Univ Lviv Lvov Ukraine Univ Jaime I Castellon de La Plana Spain Umea Univ Umea Sweden Uppsala Univ Uppsala Sweden

ISBN: (纸本)9783031637582;9783031637599

In this article, we propose an accuracy-assuring technique for finding a solution for unsymmetric linear systems. Such problems are related to different areas such as image processing, computer vision, and computational fluid dynamics. parallel implementation of Krylov subspace methods speeds up finding approximate solutions for linear systems. In this context, the refined approach in pipelined BiCGStab enhances scalability on distributed memory machines, yielding to substantial speed improvements compared to the standard BiCGStab method. However, it's worth noting that the pipelined BiCGStab algorithm sacrifices some accuracy, which is stabilized with the residual replacement technique. This paper aims to address this issue by employing the ExBLAS-based reproducible approach. We validate the idea on a set of matrices from the SuiteSparse Matrix Collection.

关键词： Krylov subspace methods BiCGStab Residual replacement Numerical reliability ExBLAS HPC

来源：评论

学校读者我要写书评

暂无评论

image Compression and Reconstruction Based on Quantum Network

Image Compression and Reconstruction Based on Quantum Networ...

引用

1st International conference on Smart Energy Systems and Artificial Intelligence (SESAI)

作者： Ji, Xun Liu, Qin Huang, Shan Chen, Andi Wu, Shengjun Nanjing Univ Sch Phys Natl Lab Solid State Microstruct Nanjing 210093 Peoples R China Nanjing Univ Collaborat Innovat Ctr Adv Microstruct Nanjing 210093 Peoples R China Nanjing Univ Inst Brain Sci Nanjing 210023 Peoples R China Nanjing Univ Kuang Yarning Honors Sch Nanjing 210023 Peoples R China Univ Sci & Technol China Hefei Natl Lab Hefei 230088 Peoples R China

ISBN: (纸本)9798350364613;9798350364606

Quantum network is an emerging type of network structure that leverages the principles of quantum mechanics to transmit and process information. Compared with classical data reconstruction algorithms, quantum networks make image reconstruction more efficient and accurate. They can also process more complex image information using fewer bits and faster parallel computing capabilities. Therefore, this paper will discuss image reconstruction methods based on our quantum network and explore their potential applications in image processing. We will introduce the basic structure of the quantum network, the process of image compression and reconstruction, and the specific parameter training method. Through this study, we can achieve a classical image reconstruction accuracy of 97.57%. Our quantum network design will introduce novel ideas and methods for image reconstruction in the future.

关键词： image compression and reconstruction quantum network parameter training

来源：评论

学校读者我要写书评

暂无评论

Efficient SpMV for Graph Matrices Through Vectoring and Caching 30th

Efficient SpMV for Graph Matrices Through Vectoring and Cach...

引用

30th European conference on parallel and distributed processing (Euro-Par)

作者： Chen, YuAng Yu, Jeffery Xu Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9783031695827;9783031695834

Sparse Matrix-Vector Multiplication (SpMV) plays a pivotal role in a wide range of scientific computations. However, SpMV operations on graph matrices often encounter challenges such as inefficient cache utilization and imbalanced workloads. This paper presents a novel solution, named VeCa, to accelerating SpMV for sparse graph matrices by integrating selective vectorization with hierarchical blocking. Firstly, the matrix is divided into small blocks fitting in the cache, where multi-level partitioning occurs according to the estimated workloads per blocks. Then, the rows within each block is selectively vectorized with distinct instruction sets. Experimental results show that VeCa considerably outperforms state-of-the-art SpMV methods and graph processing systems, achieving a speedup of 1.29x compared to the second fastest approach. Moreover, a comprehensive evaluation is conducted, analyzing performance factors, branch prediction, cache efficiency, and parameter tuning, to promote a thorough understanding of VeCa's efficacy.

关键词： SpMV SIMD Graph processing

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56页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：