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

562 篇 会议
208 篇 期刊文献
16 篇 学位论文
12 册 图书

馆藏范围

798 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

509 篇 工学
- 393 篇 计算机科学与技术...
- 211 篇 软件工程
- 104 篇 电气工程
- 55 篇 信息与通信工程
- 48 篇 光学工程
- 34 篇 电子科学与技术（可...
- 34 篇 控制科学与工程
- 29 篇 生物医学工程（可授...
- 22 篇 仪器科学与技术
- 21 篇 机械工程
- 21 篇 测绘科学与技术
- 19 篇 生物工程
- 11 篇 环境科学与工程（可...
- 7 篇 土木工程
- 7 篇 化学工程与技术
- 6 篇 材料科学与工程（可...
188 篇 理学
- 88 篇 物理学
- 72 篇 数学
- 30 篇 生物学
- 14 篇 地球物理学
- 12 篇 统计学（可授理学、...
- 10 篇 化学
- 8 篇 天文学
- 7 篇 系统科学
56 篇 医学
- 42 篇 临床医学
- 18 篇 基础医学(可授医学...
- 6 篇 特种医学
46 篇 管理学
- 38 篇 管理科学与工程(可...
- 9 篇 工商管理
- 8 篇 图书情报与档案管...
5 篇 农学
2 篇 经济学
2 篇 艺术学
1 篇 法学
1 篇 教育学
1 篇 文学

主题

103 篇 image processing
66 篇 parallel process...
42 篇 feature extracti...
38 篇 image segmentati...
32 篇 image reconstruc...
31 篇 image edge detec...
29 篇 deep learning
29 篇 distributed comp...
29 篇 computer vision
27 篇 training
25 篇 computer archite...
25 篇 computational mo...
22 篇 concurrent compu...
21 篇 accuracy
20 篇 image analysis
19 篇 image color anal...
18 篇 visualization
17 篇 neural networks
17 篇 graphics process...
16 篇 graphics process...

机构

7 篇 national laborat...
5 篇 natl univ def te...
5 篇 nanjing univ sci...
5 篇 natl univ def te...
4 篇 college of compu...
3 篇 school of comput...
3 篇 natl univ def te...
3 篇 univ chinese aca...
3 篇 hong kong polyte...
3 篇 department of co...
3 篇 school of cyber ...
3 篇 university of fl...
3 篇 natl univ def te...
3 篇 sensetime res pe...
3 篇 harbin inst tech...
2 篇 nanjing audit un...
2 篇 college of compu...
2 篇 school of comput...
2 篇 school of comput...
2 篇 univ sydney sch ...

作者

12 篇 dou yong
9 篇 qiao peng
8 篇 zhigang luo
8 篇 naiyang guan
7 篇 xu kele
6 篇 yong dou
5 篇 xiang zhang
5 篇 shi hc
5 篇 zhang yi
5 篇 dacheng tao
5 篇 li hz
4 篇 luo zhigang
4 篇 camps-valls gust...
4 篇 peng qiao
4 篇 li bo
4 篇 yang jian
4 篇 zhang xiang
4 篇 wang huaimin
4 篇 ujaldon manuel
4 篇 zhang shanshan

语言

754 篇 英文
33 篇 中文
10 篇 其他
1 篇 俄文

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

共 798 条记录，以下是71-80 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：

High-Precision Encrypted image Retrieval Scheme Using Dual-Stream Convolution Feature Fusion in Cloud Computing

High-Precision Encrypted Image Retrieval Scheme Using Dual-S...

引用

International Symposium on parallel and distributed processing with Applications, ISPA

作者： Mingyue Li Liudong Zheng Jiahui Liu Ruizhong Du Chunfu Jia Hebei University Baoding China Nankai University Tianjin China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

The retrieval of encrypted images in cloud computing is a research hotspot at present. However, the existing schemes have the problem of low image retrieval accuracy since it is difficult to obtain accurate feature information through convolutional neural network from encrypted image. In this paper, a secure image retrieval method using dual-stream convolution structure for feature fusion is proposed. Specifically, the stream cryptographic image containing contour features and the Fourier transform image containing frequency domain features are used as the two inputs of the convolutional network stream, where the weighted average gate function helps to integrate the feature information in these streams to achieve a more comprehensive feature representation and improve the retrieval accuracy. Furthermore, to keep the contour features of the encrypted image, the fuzzy image and Arnold mapping algorithm are selected randomly to encrypt the encrypted image twice. Experimental evaluation on three datasets, MNIST, Fashion-MNIST and CIFAR-100, shows that the proposed encryption method has higher security than AES and stream cipher encryption. In addition, the retrieval average accuracy (mAP) of this scheme is superior to the existing methods.

关键词： Cloud computing Ciphers Accuracy Convolution image retrieval Streaming media Logic gates Encryption Convolutional neural networks Servers

来源：评论

学校读者我要写书评

暂无评论

STA-VAD: Video Anomaly Detection Utilizing Spatio-Temporal Memory and Adaptive Deformation

STA-VAD: Video Anomaly Detection Utilizing Spatio-Temporal M...

引用

International Symposium on parallel and distributed processing with Applications, ISPA

作者： Huiyu Mu Jiashuai Su Luhui Wang Jiangwei Li Yadi Wang Xianyu Zuo Henan University Kaifeng China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Classical unsupervised video anomaly detection methods learn normal patterns from normal video frames and assume significant reconstruction deviations for unforeseen anomalous video frames. These methods often introduce additional constraints to distinguish anomalies, potentially leading to higher reconstruction errors for normal instances. While specific methods have alleviated this issue by estimating multiscale deformation fields, these rely on additional background information that is susceptible to changes in the real world. In this paper, we propose a spatio-temporal relationship-based video anomaly detection STA-VAD method. By emphasizing spatio-temporal relationships in videos, our model better captures contextual information, reducing the impact of irrelevant background information. Additionally, we enhance the multiscale deformation field by adaptively adjusting it to quantify the severity of anomalies in video frames, thereby improving discrimination between normal and anomalous samples. In the widely recognized video anomaly detection datasets UCSD Ped2 and CUHK Avenue, our method demonstrates significant enhancements in accuracy and reliability, achieving state-of-the-art performance overall.

关键词： Adaptation models image recognition Deformation Interference Feature extraction Reliability image reconstruction Anomaly detection Standards Optical flow

来源：评论

学校读者我要写书评

暂无评论

Inverse Quantum Fourier Transform Inspired Algorithm for Unsupervised image Segmentation

Inverse Quantum Fourier Transform Inspired Algorithm for Uns...

引用

IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Taoreed Akinola Xiangfang Li Richard Wilkins Pamela Obiomon Lijun Qian Department of Electrical and Computer Engineering Prairie View A&M University Prairie View Texas USA

image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a novel IQFT-inspired algorithm is proposed and implemented by leveraging the underlying mathematical structure of the IQFT. Specifically, the proposed method takes advantage of the phase information of the pixels in the image by encoding the pixels’ intensity into qubit relative phases and applying IQFT to classify the pixels into different segments automatically and efficiently. To the best of our knowledge, this is the first attempt of using IQFT for unsupervised image segmentation. The proposed method has low computational cost comparing to the deep learning based methods and more importantly it does not require training, thus make it suitable for real-time applications. The performance of the proposed method is compared with K-means and Otsu-thresholding. The proposed method outperforms both of them on the PASCAL VOC 2012 segmentation benchmark and the xVIEW2 challenge dataset by as much as 50% in terms of mean Intersection-Over-Union (mIOU).

关键词：

来源：评论

学校读者我要写书评

暂无评论

ESNet: An Efficient Real-time Semantic Segmentation Network

ESNet: An Efficient Real-time Semantic Segmentation Network

引用

International Symposium on parallel and distributed processing with Applications, ISPA

作者： Renping Xie Cong He Ming Tao Kai Ding School of Computer Science and Technology Dongguan University of Technology Dongguan China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Efficient image segmentation algorithms are critical in computer vision, as they maintain high processing speeds while handling large amounts of data and providing practical solutions in resource-limited environments. While existing classical segmentation methods achieve good results, their real-time performance can be further improved. To address this issue, we propose an efficient segmentation network (ESNet) to capture extensive contextual information and improve segmentation fineness, which are two main issues in semantic segmentation, while ensuring real-time capability. Then, we first introduce an efficient context module (ECM) that effectively enlarges the effective receptive field (ERF) of the model and improves its performance in integrating contextual information. Subsequently, a skip connection with a simple feature fusion module (SFFM) is designed to provide rich detail information, thereby improving segmentation fineness. The efficacy of ESNet was evaluated on the PASCAL VOC2012 semantic segmentation dataset against several state-of-the-art methods. ESNet achieves 71.4 FPS at a resolution of 1024×2048 on a single NVIDIA GeForce RTX 3090 GPU and achieves 62.42% mIoU at a resolution of 320×480 with an extremely simple training recipe, striking a fine balance between segmentation accuracy and inference speed.

关键词： Training distributed processing Computer vision Accuracy Semantic segmentation Computational modeling Graphics processing units Rendering (computer graphics) Real-time systems Context modeling

来源：评论

学校读者我要写书评

暂无评论

A Normalized Mutual Information-based Multi-Modal Medical image Fusion Technique using Non Sub-sampled Shearlet Transform and Method Noise

A Normalized Mutual Information-based Multi-Modal Medical Im...

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 process of merging characteristics and information from multiple images to build a single, more complete representation. This approach includes multi-modal medical image fusion, which involves fusing medical images from several imaging modalities such as computed tomography (CT) scans, Positron Emission Tomography (PET) and magnetic resonance imaging (MRI). This integration improves diagnostic accuracy by using each modality's own strengths, resulting in clearer visualization of anatomical structures and clinical situations. This work utilizes CT, PET, and MRI images as modalities for the experimentation purpose. This study (M3IF-NSST-MI) aims to construct a multi modal medical image approach that combines Non Sub-sampled Shearlet Transform (NSST) and method noise to the information content in the fused image, where high pass subbands are fused using Normalized Mutual Information (NMI) based fusion strategy. NSST domain is used for its Multi-Scale Representation and shift invariance. The concept of method noise as post-processing operation that extracts the information which was missed in the initial phase. The wavelet coefficients are fused using NMI-based fusion method. This combination of NSST with NMI-based fusion and method noise provides superior results than many conventional methods. This improves overall visual and parametric quality of fusion results than many compared methods.

关键词： Visualization Accuracy Magnetic resonance imaging Computed tomography Noise Positron emission tomography Medical diagnostic imaging image fusion Mutual information Wavelet coefficients

来源：评论

学校读者我要写书评

暂无评论

Scalable SubXPCA on a distributed Platform Applied to Classification of Hyperspectral images

Scalable SubXPCA on a Distributed Platform Applied to Classi...

引用

Conference on Information and Communication Technology (CICT)

作者： Bogolu Rupa Atul Negi School of Computer and Information Sciences University of Hyderabad Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad Telangana India

ISBN: (数字)9798331531539

ISBN: (纸本)9798331531546

The exponential growth of technological advancements in satellite and airborne remote sensing is giving rise to large volumes of high-dimensional hyperspectral image data. Apache Spark is one of the most popular, extensively used and open-source distributed processing frameworks, which is proven effective in processing large volumes of remotely sensed hyperspectral images in a time-efficient manner. Open-source distributed processing frameworks have proven effective in processing large volumes of remotely sensed hyperspectral images quickly and efficiently. While computational power has been increasing, the rate of data accumulation is more than the processing capabilities. Therefore, more efficient algorithms such as dimensionality reduction are needed to process and get accurate performance for the application. This paper proposes an efficient and parallel spectral dimensionality reduction approach based on feature partitioning principal component analysis called scalable SubXPCA. We implemented scalable SubXPCA on a spark cluster distributed environment. We compared scalable SubXPCA against other distributed feature partitioning and various non-feature partitioning dimensionality reduction methods. Our experiments on different real and synthetic datasets of hyperspectral images confirm that SubXPCA classification performance is not only better than its competitors but also that the running time of SubXPCA is better in distributed processing than serial processing. As the size of the hyperspectral image dataset increased, SubXPCA showed a speed up factor of 5.7× and more in the spark cluster compared to the serial version.

关键词： Dimensionality reduction distributed processing Accuracy Satellites Partitioning algorithms Information and communication technology Sparks Hyperspectral imaging Principal component analysis Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Photogrammetric image Sequence Analysis for Deformation Measurement and Crack Detection Applied to a Shear Test on a Carbon Reinforced Concrete Member

Photogrammetric Image Sequence Analysis for Deformation Meas...

引用

International Symposium of the International Federation for Structural Concrete, fib Symposium 2023

作者： Liebold, Frank Bergmann, Sarah Bosbach, Sven Adam, Viviane Marx, Steffen Claßen, Martin Hegger, Josef Maas, Hans-Gerd Institute of Photogrammetry and Remote Sensing Technische Universität Dresden Dresden Germany Institute of Structural Concrete RWTH Aachen University Aachen Germany Institute of Concrete Structures Technische Universität Dresden Dresden Germany

ISBN: (纸本)9783031325106

This publication presents a digital image correlation (DIC) based technique applied to a shear test on a carbon-reinforced concrete member. DIC methods are based on image sequences where the first image is recorded under zero-load without deformations while further images are taken from deformed stages. The image processing starts with the computation of subpixel-precise displacement vector fields using photogrammetric image matching algorithms. In our method, instead of computing strains, another approach is used to quantify deformations and to detect cracks. The matching points are triangulated into a triangular mesh. Then, a deformation model is used that includes a split of the triangle into two parts. The relative translation between these parts is computed and is considered as deformation vector. The detection of cracks is performed by a thresholding applied to the norm of the deformation vectors. Furthermore, the deformation vector is decomposed into the components parallel and perpendicular to the crack. The decomposition requires the knowledge of the crack normal, for which a possible estimation scheme is proposed. The presented method is suitable for brittle material, and it was applied to a monocular image sequence of a shear test of a carbon reinforced concrete member. The test specimen was made of high-strength concrete and was reinforced with a multilayer carbon reinforcement. The selected shear test was intended to analyze the shear behavior of a multi-span system with a distributed load. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Carbon

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Workflow-Based Architecture for distributed Medical image AI Systems

Design and Implementation of a Workflow-Based Architecture f...

引用

IEEE International Conference on e-Business Engineering (ICEBE)

作者： Yu Ge Qi Zhang Yibin Chen Kuo-Ming Chao Pan Hu Hongming Cai School of Software Shanghai Jiao Tong University Shanghai China Computing Department University of Roehampton London United Kingdom

ISBN: (数字)9798350365856

ISBN: (纸本)9798350365863

Medical image AI Systems can assist doctors in making diagnoses, thereby improving diagnostic accuracy. These systems are now widely used in hospitals. However, current AI diagnostic methods typically rely on various deep learning technologies, which require substantial computational resources. When diagnostic demands surge, traditional monolithic architectures may suffer from low computational performance and queue congestion. To address these issues, this paper compares and analyzes two system architectures based on parallel computing and distributed computing. The first one is a coarse-grained multi-service instance architecture, which uses clustering to expand the system's service instances, though it still presents some challenges. The second is a fine-grained workflow-based distributed architecture, which abstracts the diagnostic process into a workflow divided into several subtasks managed and scheduled by the cluster. This architecture demonstrates advantages in several aspects. Finally, this paper implements a Medical image AI System for pulmonary fibrosis diagnosis based on the workflow-based distributed system architecture.

关键词： Deep learning Hospitals Lungs Systems architecture Computer architecture parallel processing Artificial intelligence distributed computing Surges Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Transfer Learning Approaches For Medical image Analysis

A Comparative Study of Transfer Learning Approaches For Medi...

引用

International Conference on parallel distributed and Grid Computing (PDGC)

作者： Prince Priya Malla Sudhakar Sahu School of Electronics Engineering Kalinga Institute of Industrial Technology Bhubaneswar Odisha India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Deep learning based approaches have been extensively used for the image classification task with improved accuracy and lower computational complexity. The deep learning approaches have shown outstanding performances when a huge amount of datasets are available to train the model. However, in medical image analysis, sufficient data is not available to train deep learning models. To overcome these issues, a new approach called transfer learning has been introduced for the medical image classification task. This approach has shown outstanding performances with less computational complexity. In the case of transfer learning approaches, the knowledge acquired by training the model with a non-medical image dataset can be transferred to the target dataset. This paper presents a comparative study on the application of transfer learning techniques for the medical image analysis task. This paper demonstrated a complete analysis of the architecture and performance of numerous pre-trained models on the imageNet dataset. Further, This paper presents the significance of the transfer learning techniques for medical image processing tasks for example brain tumor detection, pneumonia classification, and COVID-19 detection by analyzing various state-of-the-art methods. The experimental results indicate that the performance of transfer learning-based methods can be improved by fine-tuning these models using medical-specific datasets.

关键词： Deep learning Analytical models Accuracy Computational modeling Transfer learning Brain modeling Medical diagnosis Computational complexity Medical diagnostic imaging image classification

来源：评论

学校读者我要写书评

暂无评论

Frequency-Domain Guided Multiple parallel Kernels Network for Low-Light Remote Sensing image Enhancement

Frequency-Domain Guided Multiple Parallel Kernels Network fo...

引用

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

作者： Jingxuan Zhou Hao Li Jinlong Wang Xiongxin Tang Fanjiang Xu Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Due to dark environments, optical aberrations, etc, the remote sensing images are often submerged under low contrast degradation, which greatly hinders their practical applications for agricultural management and other related tasks. The surface features of remote sensing images are often continuously distributed in space, thus, the sizes of the network’s receptive fields and its ability to learn long-range dependencies are crucial for restoring low-light remote sensing images. Existing methods based on CNN provide limited receptive fields, while Transformer-based methods are constrained by their quadratic computational complexity. To cope with these issues, we propose a novel low-light remote sensing image enhancement network that combines multi-scale receptive fields with frequency-domain attention. Specifically, this network employs multiple parallel kernels of varying sizes to learn multi-scale local features in the spatial domain and complements frequency-domain information to learn global long-range correlations, which achieves local-global feature extraction and further facilitates subsequent degraded images enhancement. We have conducted extensive experiments to demonstrate that our network outperforms existing methods quantitatively and achieves exceptional visual performance, which fully highlights the effectiveness and superiority of our method in enhancing low-light remote sensing images.

关键词： Visualization Frequency-domain analysis Transforms Speech enhancement Feature extraction Transformers image restoration Kernel Remote sensing 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80页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：