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

6,813 篇 会议
647 册 图书
129 篇 期刊文献

馆藏范围

7,587 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,911 篇 工学
- 3,099 篇 计算机科学与技术...
- 1,406 篇 软件工程
- 797 篇 电气工程
- 690 篇 信息与通信工程
- 514 篇 控制科学与工程
- 301 篇 生物工程
- 283 篇 生物医学工程（可授...
- 270 篇 机械工程
- 191 篇 光学工程
- 164 篇 电子科学与技术（可...
- 145 篇 仪器科学与技术
- 140 篇 化学工程与技术
- 64 篇 安全科学与工程
- 46 篇 材料科学与工程（可...
- 42 篇 网络空间安全
- 41 篇 交通运输工程
1,224 篇 理学
- 674 篇 数学
- 357 篇 物理学
- 334 篇 生物学
- 198 篇 统计学（可授理学、...
- 147 篇 化学
- 105 篇 系统科学
561 篇 管理学
- 320 篇 管理科学与工程(可...
- 261 篇 图书情报与档案管...
- 59 篇 工商管理
276 篇 医学
- 230 篇 临床医学
- 109 篇 基础医学(可授医学...
- 75 篇 药学(可授医学、理...
66 篇 法学
- 62 篇 社会学
51 篇 艺术学
- 49 篇 设计学（可授艺术学...
42 篇 农学
21 篇 教育学
19 篇 文学
18 篇 经济学
5 篇 军事学

主题

3,174 篇 pattern recognit...
537 篇 feature extracti...
430 篇 artificial intel...
386 篇 neural networks
298 篇 machine learning
295 篇 data mining
235 篇 face recognition
224 篇 pattern matching
216 篇 support vector m...
203 篇 image segmentati...
194 篇 pattern classifi...
194 篇 computer imaging...
183 篇 computer science
183 篇 local binary pat...
168 篇 computational mo...
159 篇 computer vision
147 篇 computer applica...
147 篇 humans
145 篇 testing
144 篇 accuracy

机构

40 篇 school of comput...
38 篇 national laborat...
25 篇 indian institute...
25 篇 institute of ima...
24 篇 center for resea...
24 篇 computer vision ...
22 篇 institute of ima...
22 篇 university of ch...
21 篇 auckland univers...
21 篇 department of co...
20 篇 city university ...
20 篇 indian statistic...
19 篇 murdoch universi...
19 篇 national laborat...
19 篇 institute of com...
18 篇 king fahd univer...
16 篇 tongji universit...
16 篇 chinese academy ...
15 篇 institute for pa...
14 篇 national center ...

作者

35 篇 yang jie
31 篇 de-shuang huang
25 篇 tieniu tan
23 篇 umapada pal
21 篇 mufti mahmud
19 篇 zohreh doborjeh
19 篇 ryszard tadeusie...
19 篇 m. tanveer
19 篇 andrew chi sing ...
19 篇 kevin wong
19 篇 liang wang
18 篇 ajith abraham
18 篇 maryam doborjeh
17 篇 marcin korytkows...
17 篇 lu hanqing
17 篇 jacek m. zurada
17 篇 leszek rutkowski
16 篇 jie yang
16 篇 zhenan sun
16 篇 shamsuddin siti ...

语言

7,247 篇 英文
275 篇 其他
82 篇 中文

检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition"

共 7589 条记录，以下是811-820 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：

Implementing a Robust IoT Solution to Monitor Prone Position using Machine Learning Techniques 11

Implementing a Robust IoT Solution to Monitor Prone Position...

引用

11th IEEE international conference on Communication Systems and Network Technologies, CSNT 2022

作者： Belay, Semagn Shifere Prince, T. Beyene, Tizazu Bayih Marew, Walelegne Yirdew Kebede, Andebet Dessiewu Woldia University School of Computing Woldia Institute of Technology Ethiopia College of Science and Arts University Department of Computer Science United Arab Emirates

ISBN: (纸本)9781665480383

It is essential to monitor sleeping patterns and position in order to learn about one's health state in order to enhance it and minimize sleep apnea. The use of a bed-mounted seismometer device to track the heart and respiratory patterns, as well as physical movement and attitude, while sleeping is discussed in this paper. The Internet of Things (IoT) and its gadgets and systems are becoming a part of everyday life. They are primarily used to track everyday tasks, particularly those that are relevant to individual health and wellness. As a matter of fact, and it's becoming increasingly important throughout the COVID-19 outbreak. A intelligent tracking and warning Internet of Things system known "NEF"was updated in this work to detect on-bed movement patterns, such as the prone position, using a variety of neural network models. On-bed movement patterns were recorded from seven different participants. The models derived using deep network were the most accurate when just the prone and supine postures were included. Random forest, on the other hand, produced the greatest total proportion of properly analysis refers to a set. Beddings such as pillows and blankets are expected to be investigated in greater depth in the future. © 2022 IEEE.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Applying Reservoir computing and Machine Learning Techniques for Image Enhancement in Biomedical Imaging

Applying Reservoir Computing and Machine Learning Techniques...

引用

international conference on Smart Communications and Networking (SmartNets)

作者： Andre Slonopas Adam Beatty Yenni Djajalaksana Department of Cybersecurity American Public University Sysytem (APUS) School of Security and Global Studies (SSGS) Charles Town WV International Council of E-Commerce Consultants (EC-Council) Academia Division Tampa FL

ISBN: (数字)9798350385328

ISBN: (纸本)9798350385335

The paper presents a comprehensive study on the application of Machine Learning (ML) in enhancing the contrast of biomedical images. This research is pivotal in addressing the challenges of low visibility and detail in medical imaging, which are crucial for accurate diagnosis and treatment. The paper introduces innovative ML-based Histogram Equalization (ML - HE), leveraging deep learning algorithms and advanced image processing methods, to significantly improve the quality of biomedical images. These techniques enhance image clarity, detail, and overall contrast without compromising the integrity of the original data. This paper seeks to explore the integration of ML, specifically Reservoir computing, with traditional image enhancement methods, creating a synergistic approach that leverages the strengths of both ML and conventional techniques and expedites image enhancements in near real-time. This hybrid approach is shown to be more effective in handling diverse and complex imaging scenarios encountered in biomedical applications. The study also discusses the implications of these advancements for medical professionals, highlighting how ML-enhanced images can lead to more accurate diagnoses, better patient outcomes, and advancements in medical research. Overall, this paper sheds light on the transformative potential of ML in revolutionizing biomedical imaging, setting a new standard for image quality and diagnostic precision in healthcare.

关键词： Histograms Visualization Accuracy Machine learning algorithms soft sensors Thermocouples Speech recognition

来源：评论

学校读者我要写书评

暂无评论

One-shot Distributed Algorithm for Generalized Eigenvalue Problem 22

One-shot Distributed Algorithm for Generalized Eigenvalue Pr...

引用

8th international conference on computing and Artificial Intelligence, ICCAI 2022

作者： Lv, Kexin Sun, Zheng He, Fan Huang, Xiaolin Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China Quality and Business Operation Department Saic Motor Corporation Limited 489 Wei Hai Road Shanghai200041 China

ISBN: (纸本)9781450396110

Nowadays, more and more datasets are stored in a distributed way for the sake of memory storage or data privacy. The generalized eigenvalue problem (GEP) plays a vital role in a large family of high-dimensional statistical models. However, the existing distributed method for eigenvalue decomposition cannot be applied in GEP for the divergence of the empirical covariance matrix. Here we propose a general distributed GEP framework with one-shot communication for GEP. If the symmetric data covariance has repeated eigenvalues, e.g., in canonical component analysis, we further modify the method for better convergence. The theoretical analysis on approximation error is conducted and the relation to the divergence of the data covariance, the eigenvalues of the empirical data covariance, and the number of local servers is analyzed. Numerical experiments also show the effectiveness of the proposed algorithms both in the synthetic dataset and real-world datasets. © 2022 ACM.

关键词： Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

Spatial-Temporal Graph Neural Networks Fusing Multiple Data 4

Spatial-Temporal Graph Neural Networks Fusing Multiple Data

引用

4th international conference on Frontiers Technology of Information and Computer, ICFTIC 2022

作者： Xu, Haonan Xue, Wenfang Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Beijing China

ISBN: (纸本)9798350321951

Recently, quantitative investment has become a new way of investment finance, which combines the model with the computer to predict the investment stock trend more efficiently and accurately. Stock trend forecasting is one of the difficult and important tasks in modern quantitative investment systems. With the development of artificial intelligence technology, many deep learning models have emerged. The application of deep learning in the stock market not only reduces the difficulty of stock analysis and trend prediction, but also introduces new investment methods and ideas for investors. However, most of the models are based on volume and price data, and the consideration of stock relationships are relatively simple, so we propose a Spatial-Temporal Graph Neural Network model fusing Barra factors (BSTGNN), which integrates factor knowledge, mines potential inter-stock relationships, and fully consider the heterogeneity of the relationship. The experiments conducted on the real-world stock market dataset prove that BSTGNN perform better than the baseline methods. © 2022 IEEE.

关键词： Investments

来源：评论

学校读者我要写书评

暂无评论

Spotting Fake News: Simplified LSTM Detection

Spotting Fake News: Simplified LSTM Detection

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Prajakta Tate Shreya Thorvat Amit Pawar Roshani Raut Anita Devkar Dept. of Information technology Pimpri Chinchwad College of Engineering Pune India

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

In the realm of combating misinformation, this paper presents a cutting-edge strategy that amalgamates two disparate datasets and sophisticated deep learning methodologies, primarily networks with long short-term memory (LSTM). Our innovative approach addresses the critical necessity for robust detection mechanisms amidst the rampant spread of fake news, particularly impacting social and political landscapes. Through meticulous experimentation, we have demonstrated substantial enhancements in accuracy and generalization, leveraging the inherent capabilities of LSTM networks and integrating diverse datasets sourced from reputable fact-checking entities and prominent social media platforms. Furthermore, we meticulously assess and benchmark our methodology against contemporary techniques, showcasing its superior efficacy in discerning authentic information from falsified narratives. Additionally, our research delves into exploring the potential synergies of user behavior analysis, social network scrutiny, and linguistic pattern recognition to further bolster detection performance. By advancing the field of bogus news detection, our study lays a formidable groundwork for mitigating the adverse consequences of disinformation in today's interconnected society pattern recognition to improve detection efficiency even more. Our study establishes a strong foundation for reducing the negative effects of misinformation in today's connected society by advancing the field of fake news detection.

关键词： Deep learning Resistance Measurement Technological innovation Accuracy Social networking (online) pattern recognition

来源：评论

学校读者我要写书评

暂无评论

2021 international conference on Advanced Computer Applications, ACA 2021

2021 International Conference on Advanced Computer Applicati...

引用

2021 international conference on Advanced Computer Applications, ACA 2021

ISBN: (纸本)9781665435031

The proceedings contain 45 papers. The topics discussed include: another certain forms of soft compact and soft closed spaces;iris features extraction and recognition based on the local binary pattern technique;design and enhancement of localization system for radio frequency emitters based on doa techniques and triangulation centroid algorithm;ensemble-based noise filter for noisy and imbalanced data;blockchain and smart contracts to improve dental healthcare for children in primary school;recommender systems for e-commerce in online video advertising: survey;and spatial domain block based blind image watermarking for hardware applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

CDE-Net: A semi-supervised nucleus instance segmentation method based on center deviation estimation 22

CDE-Net: A semi-supervised nucleus instance segmentation met...

引用

8th international conference on computing and Artificial Intelligence, ICCAI 2022

作者： Yan, Yi Wang, Da-Han Ye, Haili Zhu, Shunzhi Li, Jianmin School of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen361024 China

ISBN: (纸本)9781450396110

Cell nucleus segmentation is an important step in the diagnosis of tumor malignancy. In the case of out-of-focus, the cell nucleus boundary tends to be blurred, which increases the difficulty of cell segmentation and marking. Therefore, in the case of marking only some core instances, it is very important to realize the segmentation of core instances. In this paper, we propose a semi-supervised nucleus instance segmentation method based on anchor bias prediction that is achieved by our proposed center deviation estimation network (CDE-Net). By introducing the CDE branch to predict the offset degree of the anchor frame, and weighting the confidence of the anchor frame, more accurate prediction results can be obtained. The model adopts the semi-supervised training method to progressively learn the CDE-Net model, which alleviates the problem of imbalance between positive and negative samples caused by only marking part of the nuclear samples. The experimental results show that CDE-Net is superior to Mask R-CNN in many evaluation indicators, and achieves SOTA on the partially labelled MoNuSeg data set. © 2022 Association for computing Machinery. All rights reserved.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Autoencoder Integrated Feedforward Neural Network based Intrusion Detection System

Autoencoder Integrated Feedforward Neural Network based Intr...

引用

Advances in Signal Processing, Power, Communication, and computing (ASPCC), IEEE international conference on

作者： Piyush Raj Tushar Prakash Sonu Kumar Ankit Raj Aditya Prakash Mamata P. Wagh Computer Science and Engineering C. V. Raman Global University Bhubaneswar India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

In today’s digital world cyber security is a prominent need. Intrusion Detection system (IDS) is a vital component of cyber security. In this regard, IDS is proposed in this work which combines Autoencoders and Feedforward Neural Network(FNN) to improve security. Autoencoders efficiently extract important features from network datasets, while FNNs are skilled at recognizing complex attack patterns. By merging technologies, proposed model enhances traditional IDSs, boosting their ability to detect new and advanced cyber threats. This comprehensive approach enables to identify subtle changes in attack behaviours, effectively reducing cybersecurity risks. The experimental results confirm that our proposed model outperforms conventional models in terms of overall performance, showing higher detection rates and lower false positive rates. The proposed model is evaluated on the dataset CICIDS 2017. The accuracy of this model is 99.60% on a dataset.

关键词： Computational modeling Autoencoders Merging Intrusion detection Signal processing Feature extraction Boosting Feedforward neural networks pattern recognition Computer crime

来源：评论

学校读者我要写书评

暂无评论

Unveiling Fuzzy Topologies: Innovative Approaches to Topological Structures via Fuzzy Binary Relations

Unveiling Fuzzy Topologies: Innovative Approaches to Topolog...

引用

Women in computing (InCoWoCo), international conference for

作者： Gnanachandra P Arunthathi C Ananda Priya B Seenivasan M Centre for Research and Postgraduate studies in Mathematics Ayya Nadar Janaki Ammal College (Affliated to Madurai Kamaraj University) Sivakasi India DDE-Mathematics Wings Annamalai University Chidambaram India

ISBN: (数字)9798331518943

ISBN: (纸本)9798331518950

In order to extend classical topology to more flexible and uncertain contexts where membership to sets is not strictly binary, the idea of fuzzy topological spaces is essential. This study presents a novel fuzzy topological structure derived from fuzzy binary relations, offering a broader framework for examining elemental interactions in these kinds of spaces. Fuzzy closure and interior operators that are formed from the binary relations are used to define the new structure. Several examples demonstrate the efficiency and adaptability of this method. An analysis is conducted on the fundamental properties of the resulting fuzzy topology., which include the relationships between the smallest open sets, closure, and interior. Additionally, the study offers important corollaries and theorems that characterize the behavior of these operators and help to clarify the underlying topological structure. These findings provide fresh insights into the study of fuzzy relations and their applications in a variety of domains, including fuzzy logic systems, data analysis, and decision theory, in addition to expanding upon established properties from classical topology.

关键词： Fuzzy logic Uncertain systems Image segmentation Fuzzy sets Fuzzy control Uncertainty Network topology Decision making Topology pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Determination of pattern recognition Problems based on a Pythagorean Fuzzy Correlation Measure from Statistical Viewpoint 13

Determination of Pattern Recognition Problems based on a Pyt...

引用

13th international conference on Advanced Computational Intelligence (ICACI)

作者： Ejegwa, Paul Augustine Feng, Yuming Wen, Shiping Zhang, Wei Chongqing Three Gorges Univ Key Lab Intelligent Informat Proc & Control Chongqing 404100 Peoples R China Chongqing Three Gorges Univ Sch Comp Sci & Engn Chongqing 404100 Peoples R China Univ Technol Sydney Australian AI Inst Ultimo NSW 2007 Australia Chongqing Three Gorges Univ Sch Three Gorges Artificial Intelligence Chongqing 404100 Peoples R China Univ Agr Dept Math Stat Comp Sci PMB 2373 Makurdi Nigeria

ISBN: (纸本)9781665412544

By considering all the three parameters describing Pythagorean fuzzy set, we introduce a new technique of computing correlation coefficient between Pythagorean fuzzy sets from statistical perspective. The correlation coefficient value obtain via this technique shows strength of correlation between the Pythagorean fuzzy sets and indicates whether the Pythagorean fuzzy sets under consideration are related negatively or positively in contrast to other existing correlation coefficient approaches in Pythagorean fuzzy context, which only assess the strength of relationship. Certain numerical examples are considered to ascertain the authenticity of this method over similar techniques studied in intuitionistic/Pythagorean fuzzy contexts. Some pattern recognition problems are resolved with the aid of the new technique. For higher productivity sake, this technique could be approached from an object-oriented perspective.

关键词： correlation coefficient intuitionistic fuzzy set Pythagorean fuzzy set pattern recognition

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 << < 78 79 80 81 82 83 84 85 86 87 > >>

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：