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

15,153 篇 会议
233 篇 期刊文献
229 册 图书
3 篇 学位论文

馆藏范围

15,618 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

8,092 篇 工学
- 5,417 篇 计算机科学与技术...
- 2,792 篇 软件工程
- 2,445 篇 电气工程
- 1,573 篇 信息与通信工程
- 1,006 篇 控制科学与工程
- 833 篇 光学工程
- 572 篇 电子科学与技术（可...
- 552 篇 生物医学工程（可授...
- 549 篇 机械工程
- 507 篇 仪器科学与技术
- 414 篇 生物工程
- 285 篇 测绘科学与技术
- 204 篇 航空宇航科学与技...
- 189 篇 交通运输工程
- 180 篇 材料科学与工程（可...
- 145 篇 安全科学与工程
- 119 篇 化学工程与技术
4,111 篇 理学
- 2,774 篇 物理学
- 1,130 篇 数学
- 467 篇 生物学
- 325 篇 系统科学
- 271 篇 统计学（可授理学、...
- 146 篇 化学
1,618 篇 医学
- 1,440 篇 临床医学
- 215 篇 特种医学
- 201 篇 基础医学(可授医学...
- 134 篇 药学(可授医学、理...
858 篇 管理学
- 515 篇 管理科学与工程(可...
- 378 篇 图书情报与档案管...
- 130 篇 工商管理
77 篇 法学
68 篇 农学
42 篇 经济学
40 篇 教育学
27 篇 文学
25 篇 军事学
20 篇 艺术学
1 篇 哲学

主题

2,703 篇 image processing
1,407 篇 image segmentati...
1,150 篇 signal processin...
805 篇 real-time system...
750 篇 feature extracti...
748 篇 cameras
552 篇 image edge detec...
540 篇 signal processin...
478 篇 image reconstruc...
470 篇 image coding
447 篇 algorithm design...
377 篇 deep learning
370 篇 object detection
345 篇 hardware
344 篇 computer vision
339 篇 accuracy
337 篇 image color anal...
335 篇 real time system...
333 篇 clustering algor...
317 篇 computer archite...

机构

22 篇 signal and image...
19 篇 samara national ...
17 篇 school of electr...
12 篇 information syst...
11 篇 samara national ...
11 篇 univ texas san a...
11 篇 department of el...
11 篇 school of electr...
10 篇 department of el...
10 篇 electrical compu...
9 篇 school of electr...
9 篇 institute of ima...
9 篇 tongji universit...
9 篇 purdue univ sch ...
9 篇 university of ch...
9 篇 center for signa...
8 篇 shanghai jiao to...
8 篇 information syst...
8 篇 university of to...
8 篇 image processing...

作者

22 篇 anon
13 篇 de-shuang huang
12 篇 jagdish chand ba...
11 篇 jie yang
11 篇 p. pirsch
10 篇 hannig frank
10 篇 panetta karen
10 篇 c.-c.j. kuo
10 篇 j.m. mendel
10 篇 plaza antonio
10 篇 r. chellappa
9 篇 semenishchev e.
9 篇 zelensky a.
9 篇 bovik alan c.
9 篇 wei li
8 篇 frank hannig
8 篇 yves wiaux
8 篇 a.s. willsky
8 篇 mahalanobis a
8 篇 ilias maglogiann...

语言

14,979 篇 英文
539 篇 其他
90 篇 中文
26 篇 土耳其文
4 篇 俄文
3 篇 葡萄牙文
2 篇 法文
1 篇 西班牙文

检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VI"

共 15618 条记录，以下是801-810 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：

Neural Gas Counter Propagation Neural Network (NG CPNN): A Novel Model for Face Recognition

Neural Gas Counter Propagation Neural Network (NG CPNN): A N...

引用

2024 International conference on Science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Olagunju, Kazeem Michael Samuel Falohun, Adeleye Oke, Alice Oluwafunke Adebiyi, Marion O. Landmark University Directorate of Centre for Systems and Information Services Omu-Aran Nigeria LAUTECH Department of Computer Engineering Ogbomoso Nigeria Landmark University Department of Computer Science Omu-Aran Nigeria

ISBN: (纸本)9798350358155

The advent of biometric technology has enhanced security in various ways, especially by lowering the propensity for circumvention which was obtainable in traditional recognition measures such as the use of passwords, tokens, smart cards, PIN etc. Particularly facial recognition is currently a hot topic, which has evolved over time. A face recognition system is supposed to automatically recognize faces in pictures and videos by receiving a two-dimensional face image as input and comparing it to a predefined database of faces to outputs a discernible face image in the end. Despite the various algorithms used in face recognition, the problems of occlusion, light conditions and facial variation still persist. However, this study has implemented and presented Neural Gas Counter Propagation Neural Network (NG CPNN) as a novel model for face recognition *** implementation of model was carried out using 600 face images, pre-processed by histogram equalization, while face features were extracted by Principal Component Analysis. The novelty of NG CPNN was established by utilizing computational time, sensitivity, and accuracy as performance assessment measures at four distinct threshold values. The result shows computation time of 72.36s, accuracy of 96.25%, sensitivity of 98.33% at 0.8, 0.8, and 0.2 thresholds respectively. Finally, it was concluded based on empirical result and statistical evidence that NG-CPN is a novel model for face recognition. NG CPNN can be employed in access control systems, international borders, smartphone technology, and many more. © 2024 IEEE.

关键词： artificial intelligence biometrics face recognition image processing NG- CPNN pattern recognition

来源：评论

学校读者我要写书评

暂无评论

End-to-end Multi-source image Phase Retrieval 3

End-to-end Multi-source Image Phase Retrieval

引用

3rd IEEE International conference on Computer systems, ICCS 2023

作者： Zhao, Nan Song, Tianyang Guo, Yina Taiyuan University of Science and Technology Shanxi China

ISBN: (纸本)9798350313666

The phase information of multi-source hybrid images is prone to confusion during image propagation. Since traditional phase retrieval algorithms require a large number of assumptions that cannot be executed by obtaining amplitude, which makes phase retrieval of multi-source mixed images with phase distortion challenging. To address these phase retrieval problems, inspired by dual learning, we propose an end-to-end phase retrieval algorithm based on Multi-source image Phase Retrieval via dual Generative Adversarial Networks (MPRDGAN). By introducing the Least Square Error in the loss function of the network, the algorithm improves the performance of the model to prevent overfitting and ensures the phase retrieval of multi-source mixed images. Experimental results show that the MPRDGAN algorithm reduces the image restoration error, so that the correlation of restored images can reach more than 94.5%, which is widely used in various images such as face and remote sensing. © 2023 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Nature-Inspired algorithms for image Enhancement

Nature-Inspired Algorithms for Image Enhancement

引用

IEEE International Midwest Symposium on Circuits and systems (MWSCAS)

作者： Dhruve, Keyuri Kaur, Devinder Univ Toledo EECS Dept Toledo OH 43606 USA

ISBN: (纸本)9781665424615

The paper presents a comparative analysis of nature inspired Artificial Bee Colony and Particle Swarm Optimization algorithms for the enhancement of images. The paper briefly reviews the swarm-based algorithms. It describes the dynamics of ABC and Particle Swarm Optimization algorithm and mapping for image enhancement. The key purpose of image processing is to extract essential features from images. During an image processing operation, the input given is an image, and its output is an enhanced high-quality image based on some characteristics/features related to that image. The mapping of the ABC and PSO algorithms for image enhancement was implemented using the Matlab image processing toolbox. For both algorithms ABC and PSO, the parameters of Contrast Enhancement alpha was set in the range of 0-255 and beta was set in the range of 1-109. Finally, the Comparative Analysis of ABC and PSO algorithms was done using the metrics of Entropy, MSE and PSNR values for the images. It is found that ABC yields a better performance as compared to PSO.

关键词： component formatting style styling insert

来源：评论

学校读者我要写书评

暂无评论

An Overview of Different Approaches used for processing Satellite images

An Overview of Different Approaches used for Processing Sate...

引用

2024 International conference on Distributed systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Chethana, V. Rashmi, S. Visvesveraya Technological University Dayananda Sagar College of Engineering Department of Information Science & Engineering Belagavi India Visvesveraya Technological University Dayananda Sagar College of Engineering Department of Computer Science & Engineering (Data Science) Belagavi India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

In country such as India due to monsoon and frequent climatic changes leads to natural disasters such as floods, drought, landslides, cyclones, forest fire, earthquake and so on. The post disaster badly impacts on human life, economy and environment. As remote sensing technology advanced, the satellite images with high resolution can be processed and analyzed to get the required results. These analyzed results can be used for rescue operations after disaster or to predict any disasters before their occurrences. Some of the applications such as post disaster event management widely use onboard processing to get faster analyzed results. Various operations such as satellite image- enhancement, compression, classification and segmentation are performed on satellite images. Results of these techniques mainly used in applications such as disaster management, Land Use Land Cover, Change detection, landslide and many more. In recent days, satellite image processing are performed using new technical aspects such as deep learning, Artificial intelligence and machine learning to get fast and more accurate results. Edge-Computing-Enabled Deep Learning and Leveraging Deep Learning are the approaches used for satellite image enhancement. Panoptic Segmentation of Multispectral Satellite images approaches are mainly used for satellite image segmentation. Deep Learning based approach and Genererative Adverserial Network architecture are applied to get change detection in satellite images. Lossless algorithm for hyperspectral data compression and Neural network lossy compression techniques are preferably used for satellite image compression. Approaches such as Hybrid data model centric approach and Multiscale Convolutional Neural Network are applied to perform object detection. And also machine learning algorithms are mainly used for classification of satellite images. This paper provides comparative study survey on these various approaches used for processing of satellite images. ©

关键词： convolutional neural network deep learning disaster remote sensing satellite images

来源：评论

学校读者我要写书评

暂无评论

A Comparison on Dental X-ray Segmentation based on Fuzzy Clustering for ADIS System

A Comparison on Dental X-ray Segmentation based on Fuzzy Clu...

引用

2022 International conference on Computing, Communication, Security and Intelligent systems, IC3SIS 2022

作者： Joy, Manoj T. Shan, B. Priestly Shaji, Liyan Grace Sathyabama Institute of Science Technology Computer Science Engineering Chennai India Chandigarh University Mohali Dean Academic Affairs Punjab India Amal Jyothi College of Engineering Kanjirappally India

ISBN: (数字)9781665468831

ISBN: (纸本)9781665468831

image segmentation in image processing is the method by which images are divided into different segments. Many methods are available and one of the commonly used method are fuzzy-based systems. This paper ignites light into different fuzzy clustering methods, used for the segmentation of dental radiographs. Fuzzy C-means (FCM), Semi-Supervised fuzzy clustering with spatial constraints (SSFC-SC) and Fuzzy Level Set Algorithm (SFC-LM) are discussed in this paper for the automated dental radiograph segmentation. The three algorithms give different performance rate based on time and accuracy. These algorithms are evaluated against a real dental radiograph dataset available, and this set contains panoramic and periapical radiographs. The proposed study help in identifying the strengths and weakness of the algorithms. From the comparisons, it is inferred that the SSFC-SC based systems fair better than its counterparts. © 2022 IEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Score Level Fusion Based on T-Norms Algorithm

Score Level Fusion Based on T-Norms Algorithm

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： Hellal Leila Naceur-Eddine Boukezzoula Mohamed Cheniti LTS Laboratory University Ferhat Abbas Setif Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Multimodal biometric systems unite data from multiple biometric sources to surmount the limitations of individual systems. This paper presents an efficient algorithm for extracting details based on the image representation of fingerprints. Additionally, we conduct an in-depth investigation of T-Norm algorithms and offer a comprehensive score-level merging analysis. This analysis combines matching outcomes derived from the left and right fingerprints using the Hammacher, Schweizer-Sklar, Dombi, and Yager algorithms. The latter approaches are compared based on the receiver operating characteristic curve. The experimental evaluation conducted on the NIST fingerprint database validates the efficacy of fusion at the score level. Furthermore, it demonstrates the effectiveness of the proposed algorithm when compared to other T-Norms.

关键词： Databases Merging Signal processing algorithms Receivers Fingerprint recognition Signal processing NIST

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of techniques for extracting features from the object in image processing 5

A comparative analysis of techniques for extracting features...

引用

5th IEEE International conference on Advanced systems and Emergent Technologies (IC_ASET)

作者： Hafsia, Touka Tlijani, Hatem Nouri, Khaled Polytechn Sch Tunisia Adv Syst Lab BP 743 La Marsa Tunisia Natl Engn Sch Tunis Automat Res Lab BP 37 El Manar campus Tunis Tunisia

ISBN: (纸本)9781665427357

visual informations is very rich to control and pursue mobile robots, like wheeled mobile robots, underwater robots and aerospace mobile robots, etc. These are considered as mobile robots that move in different spaces, their main problem in this case is navigation especially in unknown environments. In effect, this navigation is possible only by the localisation and orientation of the robot by using different embedded sensors. We have the camera which is a necessary sensor in this work, it is an embedded instrument that gives very rich visual information as a sensor complementing the other sensors. In this context, the recognition of objects from visual informations is a main function among the functions very useful in image processing tasks due to its varied applications in the field of robotics. Based on the analysis of this informations and the determination of image features like color or shape or object primitives (points, lines, edges, etc.) or some other features. What interest us in this paper, various feature extraction techniques and classification of point and edge detection are discussed which are required for object recognition showing advantages and disadvantages of the selected algorithms. So, points and edge detection refers to the process of identifying and detecting sharp discontinuities in an image. In this work, we try to develop a novel algorithm using the work on the existing to create a novel detector.

关键词： image image processing Features Point Edge Detector

来源：评论

学校读者我要写书评

暂无评论

An autoencoder-based deep learning model for solving the sparsity issues of Multi-Criteria Recommender System 2

An autoencoder-based deep learning model for solving the spa...

引用

2nd International conference on Machine Learning and Data Engineering, ICMLDE 2023

作者： Rajput, Ishwari Singh Tewari, Anand Shanker Tiwari, Arvind Kumar Department of CSE National Institute of Technology Patna Patna800005 India School of Computing Graphic Era Hill University Haldwani263139 India Kamla Nehru Institute of Technology Sultanpur228118 India

In recent times, recommender systems have acquired significant popularity as a solution to the issue of information overload. These systems offer personalised recommendations to users. The superiority of multi-criteria recommender systems over their single-criterion counterparts has been demonstrated, as the former are able to provide more precise recommendations by taking into account multiple dimensions of user preferences when rating items. The prevalent recommendation technique, matrix factorization of collaborative filtering, is hindered by the data sparsity problem of the user-item matrix. On the other hand, it is noteworthy that deep learning techniques have demonstrated significant potential in various research domains, including but not limited to image processing, pattern recognition, computer vision, and natural language processing. In recent times, there has been a surge in the utilisation of deep learning techniques in recommender systems, yielding promising outcomes. This study presents a novel approach to multi-criteria recommender systems through the utilisation of deep learning algorithms to mitigate the data sparsity issue. Specifically, deep autoencoders are utilised to uncover complex, non-linear, and latent relationships between users' multi-criteria preferences followed by matrix factorization technique, ultimately leading to more precise recommendations. The proposed model is evaluated by conducting the experiments on the multi-criteria dataset of Yahoo! Movies. According to the outcomes, the proposed approach outperforms the state of the art recommendation methods by generating more accurate and personalized recommendations. Also, it reduces the data sparsity up to 11% from the multi-criteria dataset. © 2024 Elsevier B.V.. All rights reserved.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Simulation Research and Development of Agricultural Products processing Process Based on Machine Learning Algorithm

Simulation Research and Development of Agricultural Products...

引用

2022 International conference on Artificial Intelligence and Autonomous Robot systems, AIARS 2022

作者： Peng, Luo Shihezi University School of Food Science and Technology Xinjiang Shihezi832003 China

ISBN: (数字)9781665454575

ISBN: (纸本)9781665454575

In recent years, with the development of science and technology and its application in agricultural production, China's agricultural science and technology have made great progress, the concept of "agricultural processing"has been mentioned, and the research on agricultural processing has also achieved fruitful results. The combination of intelligent and automated machine learning algorithms with traditional industries can promote productivity improvement on the one hand, and realize industrial upgrading and transformation on the other hand. However, in practical production applications, machine learning algorithms are restricted by factors such as high cost, and the research and application of machine learning algorithms are greatly limited. With the development of virtual simulation technology in the field of machine learning algorithm research, it provides a new way for machine learning algorithm technology to be applied to agricultural product processing. Therefore, the research on machine learning algorithms has become a trend. The development of machine learning algorithms will drive the development of modern agriculture. It is very necessary for the research of machine learning algorithms to learn algorithms. The image is converted into a data matrix, and a computer used to replace the human brain is used to analyze the image, while completing a vision related task. China's agricultural development is facing severe challenges such as rising costs, continuous deterioration of the ecological environment and high tension of resource conditions. With the deepening of machine learning algorithm research and the rapid development of machine learning algorithm technology, machine learning algorithm simulation technology, as a safe and economic experimental tool in the application of machine learning algorithm technology, plays a more and more important role. In order to make full use of the latest research results abroad and narrow the gap with the advanced level ab

关键词： Deterioration

来源：评论

学校读者我要写书评

暂无评论

Optimization of Recognition of Microorganisms Based on Histological Information Structures of images

Optimization of Recognition of Microorganisms Based on Histo...

引用

2023 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Jumanov, Isroil Safarov, Rustam Samarkand State University Department of Artificial Intelligence and Information Systems Samarkand Uzbekistan

ISBN: (纸本)9781665475952

Constructive approaches, principles, methods of identification, recognition, and classification of micro-objects with the isolation of histological microparticles and the use of geometric characteristics of images have been developed. The technology of preliminary processing of images is investigated and modified on the basis of mechanisms for extracting statistical, dynamic, specific characteristics of information, setting the values of variables, checking the similarity of micro-objects. Mechanisms for identifying contours, dividing them into segments (classes), using histological redundant information structures, recognition and classification based on a set of numerical characteristics, a database, an image database, a knowledge base, and rules are proposed. The algorithms of learning three-layer neural network, Kohonen neural network, radial-basis network, which is combined with orthogonal algebraic polynomials 5 and 7, the interpolation spline function of Daubechies 7, mechanisms for setting variables along the boundaries of acceptable values, are studied. Mechanisms have been developed for classifying images of microparticles on the basis of histological redundant information structures of images of medical objects, segmentation, highlighting informative points, comparing redundant information structures of the original image and a modal example, and searching for characteristic features. The efficiency of the generalized algorithm for the identification of micro-objects is investigated according to the criteria of information processing performance and the correctness of recognition of micro-objects. A software complex for identification, recognition, classification of images has been developed, which has been tested taking into account the conditions for processing information from medical objects presented for diagnosing and predicting tuberculosis diseases. © 2023 IEEE.

关键词： Classification (of information)

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 << < 77 78 79 80 81 82 83 84 85 86 > >>

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：