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

674 篇 会议
12 册 图书
5 篇 期刊文献

馆藏范围

691 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

451 篇 工学
- 322 篇 计算机科学与技术...
- 258 篇 软件工程
- 196 篇 信息与通信工程
- 138 篇 电气工程
- 84 篇 生物工程
- 72 篇 光学工程
- 64 篇 生物医学工程（可授...
- 34 篇 电子科学与技术（可...
- 24 篇 化学工程与技术
- 22 篇 控制科学与工程
- 19 篇 材料科学与工程（可...
- 17 篇 仪器科学与技术
- 13 篇 机械工程
- 12 篇 安全科学与工程
- 9 篇 动力工程及工程热...
- 8 篇 交通运输工程
- 6 篇 网络空间安全
235 篇 理学
- 110 篇 物理学
- 87 篇 生物学
- 85 篇 数学
- 22 篇 化学
- 19 篇 统计学（可授理学、...
- 9 篇 系统科学
104 篇 医学
- 102 篇 临床医学
- 23 篇 基础医学(可授医学...
- 20 篇 药学(可授医学、理...
- 6 篇 公共卫生与预防医...
72 篇 管理学
- 43 篇 图书情报与档案管...
- 31 篇 管理科学与工程(可...
6 篇 法学
6 篇 教育学
- 6 篇 教育学
5 篇 农学
2 篇 军事学

主题

98 篇 signal processin...
58 篇 image segmentati...
58 篇 image processing
54 篇 signal processin...
43 篇 conferences
41 篇 deep learning
38 篇 image enhancemen...
33 篇 image recognitio...
29 篇 feature extracti...
28 篇 training
24 篇 image edge detec...
24 篇 convolution
24 篇 visualization
24 篇 image color anal...
24 篇 image reconstruc...
22 篇 image coding
22 篇 image classifica...
20 篇 neural networks
18 篇 robustness
17 篇 object detection

机构

6 篇 school of inform...
6 篇 college of elect...
5 篇 key laboratory o...
5 篇 university of ch...
5 篇 nanyang technol ...
5 篇 school of mathem...
4 篇 shanghai jiao to...
4 篇 laboratory of be...
4 篇 school of electr...
3 篇 shanghai jiao to...
3 篇 michigan state u...
3 篇 college of mathe...
3 篇 tsinghua shenzhe...
3 篇 shanghai jiao to...
3 篇 national laborat...
2 篇 university of sc...
2 篇 school of comput...
2 篇 school of cyber ...
2 篇 school of mathem...
2 篇 huazhong univers...

作者

6 篇 wang chao
6 篇 yang chuansheng
5 篇 yang yueting
5 篇 wen bihan
5 篇 yang jian
4 篇 jian wang
4 篇 tan anhui
4 篇 anil kumar
4 篇 bo feng
4 篇 chao xu
3 篇 ravishankar saip...
3 篇 zhou jiantao
3 篇 li min
3 篇 zhai guangtao
3 篇 nguyen trong-the
3 篇 feng bo
3 篇 parthasarathy ra...
3 篇 xiaotao huang
3 篇 wang liu
3 篇 fan zhun

语言

691 篇 英文

检索条件"任意字段=2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021"

共 691 条记录，以下是361-370 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：

A Band Selection Method for Hyperspectral image Based on Binary Coded Hybrid Rice Optimization Algorithm 11

A Band Selection Method for Hyperspectral Image Based on Bin...

引用

11th IEEE international conference on Intelligent Data Acquisition and advanced Computing Systems - Technology and Applications (IDAACS)

作者： Ye, Zhiwei Liu, Shiqin Zong, Xinlu Shu, Zhe Xia, Xiaoyu Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781665426053

Hyperspectral image analysis is one of the most important topics in the field of remote sensing. As the band dimension of hyperspectral image increases, it may cause a curse of dimensionality. Band selection could choose a subset of bands that is the most effective for classification recognition to achieve dimensionality reduction. Furthermore, binary coding is more suitable for solving the band selection problem. Therefore, a band selection method for hyperspectral image based on binary coded hybrid rice optimization algorithm is proposed in the paper. The band selection problem is solved as a combinatorial optimization problem by defining an objective function based on the classification accuracy and the number of bands. The proposed method is compared with other nature-inspired algorithms on Indian Pines, Salinas, Kennedy Space Center, and Pavia University hyperspectral datasets. Experimental results demonstrate that the proposed method achieves satisfactory results in terms of performance and execution time for band selection.

关键词： hyperspectral image band selection hybrid rice optimization algorithm image processing

来源：评论

学校读者我要写书评

暂无评论

Analysis and Application of Multispectral image processing Techniques Applied to Soybean Crops from Drones Vision System 18

Analysis and Application of Multispectral Image Processing T...

引用

18th international conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Gonzalez, Evelio Nunez, Cristhian Salinas, Jose Rodas, Jorge Rodas, Mariela Paiva, Enrique Kali, Yassine Saad, Maarouf Lesme, Fernando Lesme, Jose Gonzalez, Luis Maldonado, Belen Rodriguez-Pineiro, Jose Univ Catolica Nuestra Senor Asuncion Unidad Pedag Caacupe Caacupe Paraguay TECHA Caacupe Paraguay Univ Nacl Asuncion Fac Ingn Lab Power & Control Syst Luque Paraguay Inst Paraguayo Tecnol Agr Caacupe Paraguay Ecole Technol Super GREPCI Lab Montreal PQ Canada Tongji Univ Coll Elect & Informat Engn Shanghai Peoples R China

ISBN: (纸本)9789897585227

Drones are important in precision agriculture applications since they represent a new tool that can increase crop production. In this context, the digital processing of the images obtained from multispectral cameras integrated into the drones makes it possible to analyze the stress state of the crops, their vigor, a burned area, among others. The latter are usually obtained through proprietary applications with very high subscription costs. For this reason, this article presents the step-by-step implementation process of the different methods or algorithms to be applied to multispectral images using the open-source Python programming language. We use a soybean crop as an example of the application, and the results obtained from applying the digital image processing algorithms are presented.

关键词： Drones Multispectral Imaging Digital signal processing Precision Agriculture

来源：评论

学校读者我要写书评

暂无评论

A Multiscale Dual-Attention based Convolutional Neural Network for Ship Classification in SAR image

A Multiscale Dual-Attention based Convolutional Neural Netwo...

引用

2021 IEEE international conference on signal processing, Communications and Computing, ICSPCC 2021

作者： Zhou, Gaoyu Zhang, Gong Fang, Zheng Dai, Qijun Ministry of Education Nanjing University of Aeronautics and Astronautics Key Lab of Radar Imaging and Microwave Photonics Nanjing China

ISBN: (纸本)9781665429184

Classical ship target classification algorithms in synthetic aperture radar (SAR) images mainly rely on manual extraction of simple physical features to distinguish different ship types. A novel multiscale dual-Attention (MDA) based convolutional neural network (CNN) is proposed in this paper to highlight the deep distinguishable features extracted from SAR images for classification. First, we apply the data enhancement method to expand the limited labeled sample set to alleviate the defect of unbalanced dataset. Second, the squeeze-And-excitation(SE) block is adopted to learn the initial weight of the feature maps to mitigate the negative effects of large similarity between different ship classes. Third, the weighted feature maps are sent into two parallel self-Attention blocks, and the semantic dependence on spatial dimension and channel dimension is modeled respectively. Feature fusion is carried out to further improve feature discrimination ability. The results of ablation experiments and comparative experiments on the open SAR ship dataset show that this method can mine deep discriminant features effectively, and further improve the classification accuracy of ships in SAR images compared with baseline method and other latest methods. © 2021 IEEE.

关键词： Ships

来源：评论

学校读者我要写书评

暂无评论

A Compendious Analysis of Advances in HE Methods for Contrast Enhancement 2nd

A Compendious Analysis of Advances in HE Methods for Contras...

引用

2nd international conference on VLSI, Communication and signal processing, VCAS 2019

作者： Vijayalakshmi, D. Nath, Malaya Kumar National Institute of Technology Puducherry Karaikal India

ISBN: (纸本)9789811568398

image enhancement is a crucial pre-processing technique for image processing applications such as satellite images, medical images, and aerial surveillance systems. The image enhancement aims to produce visual content of the image in more pleasing and more suitable for machine vision applications. Enhancement of image can be improved by either increasing the contrast of the image with a low dynamic range or by highlighting the prominent details of the image. In this paper, a comprehensive analysis of bi-histogram and two-dimensional histogram equalization-based contrast enhancement techniques is performed. The performance of the various algorithms has been validated through three different databases and various performance measures. From the compendious analysis, it can be interpreted that modeling an algorithm with lower absolute mean brightness error (AMBE) and higher contrast values can render a better-enhanced image. From the qualitative and quantitative analysis, edge enhancing bi-histogram equalization using guided image filter outperforms the other contrast enhancement techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

international conference on Big Data and Cloud Computing, ICBDCC 2021

International Conference on Big Data and Cloud Computing, IC...

引用

international conference on Big Data and Cloud Computing, ICBDCC 2021

ISBN: (纸本)9789811921766

The proceedings contain 81 papers. The special focus in this conference is on Big Data and Cloud Computing. The topics include: Blockchain for CCTV Surveillance;Intelligent Traffic Management System Using YOLO Machine Learning Model;ioT-Based Security Camera Bot Using Raspberry Pi;performance Analysis of Different Deep Learning Models for Forest Fire Classification;Secure GEDAR Routing Protocol for Underwater Data Collection Using WSN;a Comprehensive Review on Automatic image Captioning Using Deep Learning;A GAN-Based Triplet FaceNet Detection Algorithm Using Deep Face Recognition for Autism Child;Rapid Efficient Loss Less Color image Compression Using RCT Technique and Hierarchical Prediction;anonymized Questionnaire Analysis with Differential Privacy for Large-Scale Crowdsourcing;design and Development of Web-based Photoplethysmogram signal Monitoring and Human Vital Parameters Measurement;smart Fetal Health Monitor;event Location Detection from Online Clustering algorithms Using Geo-Tagged User Data in Social Streams;smart Cyberbullying Detection with Machine Learning;tourist Sentiment Analysis Using Natural Language processing;sentiment Analysis of Twitter Data Using Machine Learning;comparative Study on Recognition of Food Item from images for Analyzing the Nutritional Contents;shot Boundary Detection and Video Captioning Using Neural Networks;Ensuring the Presence of a Person During Virtual Classes Using Histogram of Oriented Gradients (HOG) Algorithm;an Optimized K-means Clustering Approach on Top of MapReduce;identification of Alzheimer’s Disease Using Principal Component Analysis-Based Data Mining Techniques;Dew Computing-Inspired Mental Health Monitoring System Framework Powered by a Lightweight CNN;feature Dimensionality Reduction Method on Social Network Dataset;Internet of Things (IoT) for Coronavirus (COVID-19) Pandemic: A Survey on Trailblazing Techniques;optical Character Recognition-Based Signboard Detection.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Parametric Analysis of CT-image-Preprocessing for Improved Performance of Post-processing Operation 10

Parametric Analysis of CT-image-Preprocessing for Improved P...

引用

10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Shivwanshi, Resham Raj Nirala, Neelamshobha National Institute of Technology Raipur Department of Biomedical Engineering India

ISBN: (纸本)9781665439701

advanced technological tools in medical image analysis for disease detection and diagnosis are progressively coming into the utility of doctors and academicians due to various methodological evolution. Since the last three decades, various studies have been performed to achieve the state of the art predictive ability through early warning disease detection systems. After going through existing research work, it has been found that there is a lack of credibility in CT (computed tomography) image disease detection algorithms, which can be overcome by applying certain image processing and statistical analysis techniques. This article is made to describe a disparate approach in order to attain eminence in terms of lung disease diagnosis and detection. There are a huge amount of databases available online, but most of them encounter the issues of image noise and quality deterioration that further becomes the cause of irregularity and erroneous outcomes. The notion of this paper is to delineate an approach to pre-process input images and measure the quality of the given technique in order to choose better image operations and improve their visual information before analyzing them through a meticulous algorithm. An amalgamation of appropriate filters and image enhancement operations are also utilized to make clear insights of abnormality present inside of lung parenchyma. Furthermore, This study shows that the application of a high pass filter in the spatial domain improves the input image quality that is clearly identified by performing statistical analysis of output parameters. It is also observed that the otsu filtered image is more suitable to prepare the image for an efficient segmentation procedure. At last, it has been discussed that the overall approach in the form of pre-processing and its parameter estimation would not only help to assure quality enhancement of input image but also assist to run disease detection precisely in order to obtain reliable outcomes. ©

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

Towards image denoising in the latent space of learning-based compression 44

Towards image denoising in the latent space of learning-base...

引用

conference Applications of Digital image processing XLIV

作者： Testolina, Michela Upenik, Evgeniy Ebrahimi, Touradj Ecole Polytech Fed Lausanne EPFL Multimedia Signal Proc Grp MMSPG CH-1015 Lausanne Switzerland

ISBN: (数字)9781510645233

ISBN: (纸本)9781510645233;9781510645226

In recent years, learning-based image compression has demonstrated similar or superior performance when compared to conventional approaches in terms of compression efficiency and visual quality. Typically, learning-based image compression takes advantage of autoencoders, which are architectures consisting of two main parts: a multi-layer neural network encoder and its dual decoder. The encoder maps the input image represented in the pixel domain to a compact representation, also known as latent space. Consequently, the decoder reconstructs the original image in the pixel domain from its latent representation, as accurately as possible. Traditionally, image processing algorithms, and in particular image denoising, are applied to images in the pixel domain before compression, and eventually in some cases as a post-processing stage after decompression. In this context, the combination of denoising operations with the autoencoder might reduce the computational cost while achieving similar performance in accuracy. In this paper, the idea of combining the image denoising task with compression is examined. In particular, the integration of denoising convolutional layers in the decoder of a learning-based compression network is investigated. Results show that, while the rate-distortion performance of the method is slightly reduced, a gain in the computational complexity can be achieved.

关键词： image denoising learning-based compression compressed domain denoising latent space image processing

来源：评论

学校读者我要写书评

暂无评论

11th international Workshop of advanced Manufacturing and Automation, IWAMA 2021

11th International Workshop of Advanced Manufacturing and Au...

引用

11th international Workshop of advanced Manufacturing and Automation, IWAMA 2021

ISBN: (纸本)9789811905711

The proceedings contain 98 papers. The special focus in this conference is on advanced Manufacturing and Automation. The topics include: signal Denoising Algorithm of Massage Chair Movement Based on iForest-EEMD;Prediction of Remaining Life of Massage Chair Movement Based on ARIMA-BP Model;real-Time Data-Driven Digital Twin Workshop Web Interactive Application;digital Twin Construction Method for Docking Mechanism Test-Bed;visualized Interaction Method of Mechanical Arm Based on Augmented Reality;research on image Acquisition Preprocessing and Data Augmentation Algorithm Based on Strip Surface Defect Detection Technology;experimental Investigation of the Effect of Ultrasonic Wave on the Saturated Hydrocarbons in Castilla Crude Oil;random Assembly Task Evaluation Based on Human-Robot Collaboration;a Review on Application of Eddy Current Separation for the Recycling of Scraped Vehicles;kanban System in Industry 4.0 Era: A Systematic Literature Review;influence of Magnetic Fluid Hydraulic Medium on Cushioning Performance of Hydraulic Cylinder;DEM-CFD Simulation for Recovering Metal Particles with Aero-Electrostatic Separator;a Bibliometric Analysis of the Logistical Challenges and Methods for Vaccine Distribution Under the Pandemic;numerical Stress Analysis and Fatigue Life Prediction of the Classical External Geneva Mechanism;tensile and Flexural Properties of Acacia Tortilis/Glass Fiber Reinforced Hybrid Composites;multi Robot Welding Path Planning Based on Improved Ant Colony Algorithm;data Acquisition and processing of Space Docking Physics Experiment Platform;Research on SDN-Based New In-vehicle Network Packet Scheduling Technology;design and Transmission Performance Analysis of a Novel Reducer with Abnormal Cycloidal Gear;noncontact Clearance Measurement Research Based on Machine Vision;Optimal Design of Truss Based on LA-GSA.

关键词：

来源：评论

学校读者我要写书评

暂无评论

image denoising algorithms using norm minimization techniques 2

Image denoising algorithms using norm minimization technique...

引用

2nd international conference on Computer Science's Complex Systems and their Applications, ICCSA 2021

作者： Diffellah, Nacira Bekkouche, Tewfik Hamdini, Rabah Dept. of Electronics Faculty of Technology University of Bordj Bou Arreridj Bordj Bou Arreridj34000 Algeria Dept. of Electromechanics Faculty of Technology University of Bordj Bou Arreridj Bordj Bou Arreridj34000 Algeria Dept. of Electronics Faculty of Technology University of Saad Dahlab Blida 01 Blida09000 Algeria

image denoising is one of the fundamental image processing problems. Noise removal is an important step in the image restoration process. In this paper, firstly we develop and implement two different image denoising algorithms based on norm minimization, namely 1 and 2-regularization applied to images contaminated by Gaussian noise. Then, after their discretization and implementation, we perform a comparison between the two methods using several test images. Through this study, the algorithm which minimizes 2-norm of gradient of image has a unique solution and it's easy to implement, but it doesn't accept contour discontinuities, causing the obtained solution to be smooth. The 2-norm will blur the edges of the image. In order to preserve sharp edges, 1-norm is introduced. There are different methods to solve the problem of energy minimization. In this work, we have chosen the discretization finite difference method before applying the gradient descent algorithm to optimize the signal (2D grayscale images) denoising functionality. Experiments results, show that 1 regularization encourages image smoothness while allowing for presence of jumps and discontinuities, a key feature for image processing because of the importance of edges in human vision. © 2021.

关键词： image denoising

来源：评论

学校读者我要写书评

暂无评论

An Optimizing Multilevel Thresholding for image Segmentation Based on Hybrid Swarm Computation Optimization 16th

An Optimizing Multilevel Thresholding for Image Segmentation...

引用

16th international conference on Intelligent Information Hiding and Multimedia signal processing, IIH-MSP 2020 in conjunction with the 13th international conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Dao, Thi-Kien Wang, Hong-Jiang Yu, Jie Nguyen, Huu-Quynh Ngo, Truong-Giang Nguyen, Trong-The Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Mechanical and Automotive Engineering Fujian University of Technology Fuzhou350118 China Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Department of Information Technology Haiphong University of Management and Technology Haiphong Viet Nam

ISBN: (纸本)9789813367562

This paper suggests a solution for the image segmentation (IS) problem with the multilevel thresholding based on one of the latest hybrid swarm computation optimization algorithms, particle swarms, and gravitational search (PSGA). The experimental results are comparable with other state-of-the-art algorithms that show that the PSGA on selected images is better than the competitors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： image segmentation

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70页 << < 33 34 35 36 37 38 39 40 41 42 > >>

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：