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41-50 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：

Edge-enhanced GAN with Vanishing Points for image Inpainting 23

Edge-enhanced GAN with Vanishing Points for Image Inpainting

引用

23rd ACIS International Summer Virtual conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing, SNPD-Summer 2022

作者： Masaoka, Kei Sari, Irawati Nurmala Du, Weiwei Kyoto Institute of Technology Department of Information Science Kyoto Japan Kyoto Institute of Technology Information and Human Science Kyoto Japan

ISBN: (纸本)9798350396379

Reconstructing the damaged images with perspective views has an extensive range in the field of image inpainting. However, most existing methods generated inadequately realistic restored images. Accomplishing this problem, we propose an edge-enhanced image generation model considering viewpoints. Our method applies edge map information to guide image generation based on the perspective views of an image using vanishing points detection. Texture synthesis will be presented as post-processing to complete the remaining missing regions. Experiment shows that our approach can generate perspective images with convincing details, such as indoor and outdoor facades. © 2022 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Towards a SOLAP Based Decision Support System for Forest Fire Management

Towards a SOLAP Based Decision Support System for Forest Fir...

引用

2023 International conference on Earth Observation and Geo-Spatial Information, ICEOGI 2023

作者： Belaroussi, Asma Derbal, Khalissa Benabdellah, Rachid Belhadj-Aissa, Mostefa Image Processing and Radiation Laboratory Ltir Usthb Algiers Algeria Lsi Laboratory Usthb Algiers Algeria General Directorate of Forestry Dgf Algiers Algeria

ISBN: (纸本)9798350396720

Risk, suppression, and damage assessment are essential parts of forest fire management. The involved data is distributed and heterogeneous, concerning meteorology, topomorphology, and socio-economy. In addition, it has a multiscale spatiotemporal analysis aspect. These reinforce the need to use the appropriate methods and technologies to enhance decision-making. This research investigates the potential of adopting spatial data warehousing techniques to build a SOLAP-based DSS that supports the whole decisional chain. (i) source collection and integration;(ii) data repository design and population;(iii) SOLAP analytics;and finally, (iv) data visualization in numerous formats, including tabular, graphic, and dynamic maps. © 2023 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Dynamic Offloading Control for Waste Sorting Based on Deep Q-Network 24th

Dynamic Offloading Control for Waste Sorting Based on Deep...

引用

24th International conference on Algorithms and Architectures for parallel processing, ICA3PP 2024

作者： Wang, Jing Wang, Xiaoyang Guo, Jianxiong Tang, Zhiqing Ding, Xingjian Wang, Tian Advanced Institute of Natural Sciences Beijing Normal University Zhuhai China Guangdong Key Lab of AI and Multi-modal Data Processing Department of Computer Science BNU-HKBU United International College Zhuhai China Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9789819615278

With the increasing concern for environmental protection and resource optimization, efficient waste sorting has become a serious challenge today. In this paper, we propose a new offloading control problem that aims to solve waste sorting in wireless bin communication networks. Due to limited computational power, bins belonging to embedded devices rely on simple classification models with varying accuracy. In this scenario, consider a network of intelligent bins, each acting as an independent agent capable of deciding to offload an image to the edge server with a more accurate but resource-intensive model when the local classification is deemed inaccurate. Thus, Our goal is to find a lightweight online offloading policy that can achieve the best possible sorting accuracy while balancing transmission traffic. The method utilizes a Deep Q-network algorithm that enables each intelligent bin to make image-processing decisions autonomously. In the experiment, we validate the effectiveness of improving the performance of waste classification compared with existing flow control methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： distributed Resource Allocation Intelligent Waste Management Waste Sorting Wireless Communication Network

来源：评论

学校读者我要写书评

暂无评论

Cuckoo Search Optimized Histogram Equalization for Low Contrast image Enhancement 7

Cuckoo Search Optimized Histogram Equalization for Low Contr...

引用

7th International conference on parallel, distributed and Grid Computing, PDGC 2022

作者： Thakur, Niveditta Khan, Nafis Uddin Sharma, Sunil Datt Jaypee University of Information Technology Solan India

ISBN: (纸本)9781665454018

image enhancement is a process to improve the visual standard of image so as to extract spatial features of image. Histogram Equalization is method by which image can be improved for better perception and interpretation by different automated image processing system and human beings. Although, for low-contrast images (with lower dynamic range) traditional histogram equalization deteriorate quality of the output image by introducing washed-out form caused by too much brightness change. This paper presents histogram equalization based image enhancement method which is optimized using cuckoo search algorithm. Foremost purpose of the proposed method is to control over and under enhancement by calculating clip limits of the image histogram before performing histogram equalization. This method uses cuckoo search algorithm to automatically control the clip limit according to the image nature using improved fitness function. Effectiveness of the proposed method in comparison to other methods is analyzed using well known image quality metrics. © 2022 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

image Inpainting using Automatic Structure Propagation with Auxiliary Line Construction 23

Image Inpainting using Automatic Structure Propagation with ...

引用

23rd ACIS International Summer Virtual conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing, SNPD-Summer 2022

作者： Urano, Yuto Sari, Irawati Nurmala Du, Weiwei Kyoto Institute of Technology Department of Information Science Kyoto Japan Kyoto Institute of Technology Information and Human Science Kyoto Japan

ISBN: (纸本)9798350396379

Existing image inpainting methods used traditional and deep learning methods to restore a large missing region in the damaged image. This often leads to color discrepancy and blurriness. Pre-processing of prior line detection by user assistance is usually employed to reduce the blurry of center region by segmenting the large region into more minor. However, it operates manually, which is time-consuming. This paper introduces a technique to generate two-line types: penetrator and interactor in constructing auxiliary lines as guidance. These lines assist structure propagation established automatically, while the remaining small regions are filled by texture propagation. Experiments on large regular masks demonstrate that our proposed approach generates higher-quality results than other methods. © 2022 IEEE.

关键词： Textures

来源：评论

学校读者我要写书评

暂无评论

引用

4th International conference on Information Science, parallel and distributed Systems, ISPDS 2023

作者： Zhou, Ya Zhao, Ning Huang, Guimin Deng, Nanxiao Guo, Qingkai School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China

ISBN: (纸本)9798350337181

In sentence similarity research methods, sentence similarity is often calculated from semantic aspects, however, the influence of other features is ignored. For example, the influence of sentence syntactic structure and word order on sentence similarity is not considered. Therefore, This paper proposes a method to measure the degree of similarity between sentences based on a multi-feature fusion of semantics, syntactic similarity and word order similarity, respectively. For the aspect of semantic similarity, in this paper, we first preprocess the sentence and obtain the word vectors, and then obtains sentence vector features through neural networks, so as to calculate the sentence semantic similarity;Finally, for the aspect of word order similarity, word order is considered as the auxiliary feature information to calculate sentence similarity since word order has a smaller effect on sentence similarity compared to the above information. The experimental results show that the proposed model has an accuracy of 77.4 % and an F1 value of 84.3% on the MRPC dataset. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Cervical cell classification based on attention mechanism and multi-resolution feature fusion 3

Cervical cell classification based on attention mechanism an...

引用

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

作者： Yu, Jingya Wang, Guoyou Cheng, Shenghua School of Automation Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multispectral Information Processing Wuhan China Britton Chance Center School of Engineering Sciences Huazhong University of Science and Technology Moe Key Laboratory for Biomedical Photonics Wuhan China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

Liquid-based thin-layer cell smears are very important for the early screening and prevention of cervical cancer, and computer-aided diagnosis can reduce the workload of pathologists. The cell classification method based on deep learning can process data efficiently. However, most classification methods are based on a single resolution for recognition. When the resolution is low, the processing speed of the whole slide image is faster, but lack of picture details, which makes the identification inaccurate. When the resolution is high, it takes more time to process the whole slide image, but with more image detail. To this end, we propose a model based on Attention Mechanism and Multi-resolution Feature Fusion Module (AMFM), which combine the advantages of various resolutions to classify cervical cells. Experiments show that the accuracy is increased by 3.93% and the AUC is improved by 0.022 on the four-classification task of the cervical cell compared to the model based on a single resolution. © 2022 IEEE.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Counterfactual Ultrasound Anti-Interference Self-Supervised Network for B-mode Ultrasound Tongue Extraction

A Counterfactual Ultrasound Anti-Interference Self-Supervise...

引用

2025 IEEE International conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Jia, Yan Cheng, Yuqing Xu, Kele Dou, Yong Qiao, Peng He, Zhouyu National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha China College of Systems Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9798350368741

B-mode ultrasound tongue imaging is a non-invasive and real-time method for visualizing vocal tract deformation. However, accurately extracting the tongue's surface contour remains a significant challenge due to the low signal-to-noise ratio (SNR) and prevalent speckle noise in ultrasound images. Traditional supervised learning models often require large labeled datasets, which are labor-intensive to produce and susceptible to noise interference. To address these limitations, we present a novel Counterfactual Ultrasound Anti-Interference Self-Supervised Network (CUAI-SSN), which integrates self-supervised learning (SSL) with counterfactual data augmentation, progressively disentangles confounding factors, ensuring that the model generalizes well across varied ultrasound conditions. Our approach leverages causal reasoning to decouple noise from relevant features, enabling the model to learn robust representations that focus on essential tongue structures. By generating counterfactual image-label pairs, our method introduces alternative, noise-independent scenarios that enhance model training. Furthermore, we introduce attention mechanisms to enhance the network's ability to capture fine-grained details even in noisy conditions. Extensive experiments on real ultrasound tongue images demonstrate that CUAI-SSN outperforms existing methods, setting a new benchmark for automated contour extraction in ultrasound tongue imaging. Our code is publicly available at https://***/inexhaustible419/CounterfactualultrasoundAI. © 2025 IEEE.

关键词： contour extraction counterfactual inference self-supervised learning speech production ultrasound image

来源：评论

学校读者我要写书评

暂无评论

Federated Semi-supervised Medical image Segmentation Based on Asynchronous Transmission 1

引用

19th International conference on Advanced Intelligent Computing Technology and Applications (ICIC)

作者： Liu, Fangbo Yang, Feng Guangxi Univ Sch Comp & Elect & Informat Nanning 530004 Guangxi Peoples R China Guangxi Univ Guangxi Key Lab Multimedia Commun Network Technol Nanning 530004 Guangxi Peoples R China Guangxi Univ Key Lab Parallel Distributed & Intelligent Comp Educ Dept Guangxi Zhuang Autonomous Reg Nanning Guangxi Peoples R China

ISBN: (数字)9789819947492

ISBN: (纸本)9789819947485;9789819947492

Most existing medical image segmentation methods under federated learning use labeled data for training. But in practice, high-quality labeled data is scarce. Due to the specialized nature of medical images, manual labeling will waste a lot of manpower and resources. In addition, due to the private nature of medical images, datasets cannot be shared between institutions. Therefore, this paper proposes a semi-supervised medical image segmentation method based on asynchronous federated learning, which purposes to learn a federated model using a small amount of labelled data and a large amount of unlabeled data. First, to generate better pseudo-labels for locally unlabeled data, we set the local as the teacher model and the global as the student model to learn data information in the multi-agency. Then, the global student model is used to guide the generation of the local teacher model and the consistency regularization is performed. In addition, we use the student model to maintain the stability of the global model. Finally, we propose an asynchronous federated algorithm and local iterator mechanism to address the high load and latency problems on the central server caused by differences between client devices in synchronous transmission. Our experiments on two medical image segmentation tasks demonstrate that the method effectively validates the feasibility of federated semi-supervised segmentation and significantly improves model segmentation performance and communication efficiency.

关键词： Federated learning Medical image segmentation Pseudo-label Asynchronous Iterator

来源：评论

学校读者我要写书评

暂无评论

A Noise-Based Approach Augmented with Neural Cleanse and JPEG Compression to Counter Adversarial Attacks on image Classification Systems

A Noise-Based Approach Augmented with Neural Cleanse and JPE...

引用

Euromicro conference on parallel, distributed and Network-Based processing

作者： Igor Kotenko Igor Saenko Oleg Lauta Nikita Vasiliev Vladimir Sadovnikov Laboratory of Computer Security Problems St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS) Saint-Petersburg Russia Department of Telecommunications and Information Security Admiral Makarov State University of Maritime and Inland Shipping Saint-Petersburg Russia

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Adversarial attacks are now becoming quite a dangerous means of disrupting image processing systems that use machine learning methods for decision making. Therefore, developing effective countermeasures against adversarial attacks is becoming quite an important area of cybersecurity. The paper proposes a noise-based approach to countering adversarial attacks that is augmented with neural-cleanse and jpeg-compression technologies. The idea of the proposed approach is that adding noise distorts the effect of an adversarial attack, and neural cleaning and jpeg compression eliminate the consequences of such an effect. The paper examines the three most well-known types of adversarial attacks: Fast Gradient Sign Method, Zeroth Order Optimization and One Pixel Attack. These attacks manipulate input data, resulting in misclassification or incorrect predictions by exploiting high-frequency components that are undetectable to humans. The research was carried out on two datasets: MNIST-JPG and PC Parts images. Two types of noise were used: Gaussian and Poisson. During the experiments, optimal parameters for these types of noise were found, ensuring maximum accuracy of image recognition after exposure to adversarial attacks.

关键词： Resistance image recognition image coding image resolution Noise Transform coding Machine learning Distortion Optimization image classification

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：