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

6,793 篇 会议
630 册 图书
130 篇 期刊文献

馆藏范围

7,552 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,899 篇 工学
- 3,090 篇 计算机科学与技术...
- 1,403 篇 软件工程
- 794 篇 电气工程
- 679 篇 信息与通信工程
- 503 篇 控制科学与工程
- 299 篇 生物工程
- 281 篇 生物医学工程（可授...
- 265 篇 机械工程
- 191 篇 光学工程
- 163 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
- 59 篇 安全科学与工程
- 45 篇 材料科学与工程（可...
- 36 篇 交通运输工程
1,222 篇 理学
- 673 篇 数学
- 356 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
553 篇 管理学
- 314 篇 管理科学与工程(可...
- 255 篇 图书情报与档案管...
- 59 篇 工商管理
274 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
- 39 篇 作物学
21 篇 教育学
19 篇 文学
18 篇 经济学
5 篇 军事学

主题

3,150 篇 pattern recognit...
535 篇 feature extracti...
429 篇 artificial intel...
385 篇 neural networks
295 篇 data mining
278 篇 machine learning
234 篇 face recognition
224 篇 pattern matching
215 篇 support vector m...
203 篇 image segmentati...
194 篇 pattern classifi...
193 篇 computer imaging...
183 篇 computer science
182 篇 local binary pat...
168 篇 computational mo...
159 篇 computer vision
147 篇 humans
146 篇 testing
142 篇 accuracy
141 篇 training

机构

40 篇 school of comput...
38 篇 national laborat...
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 department of co...
20 篇 indian statistic...
19 篇 national laborat...
19 篇 institute of com...
16 篇 tongji universit...
16 篇 chinese academy ...
15 篇 institute for pa...
14 篇 national center ...
14 篇 chinese acad sci...
14 篇 częstochowa univ...
13 篇 agh university o...
13 篇 school of electr...
12 篇 indian stat inst...

作者

35 篇 yang jie
31 篇 de-shuang huang
25 篇 tieniu tan
23 篇 umapada pal
19 篇 ryszard tadeusie...
19 篇 liang wang
18 篇 ajith abraham
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 ...
16 篇 pal umapada
15 篇 wang da-han
15 篇 chew lim tan
15 篇 rafał scherer
14 篇 xu changsheng
14 篇 lotfi a. zadeh

语言

7,403 篇 英文
84 篇 其他
77 篇 中文

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

共 7554 条记录，以下是1021-1030 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：

Key Points Positioning: A Two-Stage Algorithm For Single-view Point Cloud of Human Back Based on Point-wise Network 22

Key Points Positioning: A Two-Stage Algorithm For Single-vie...

引用

Proceedings of the 2022 11th international conference on computing and pattern recognition

作者： Nan Dong Xinfeng Zhang Xiaomin Liu Wei Guo Fei Wang Beijing University of Technology China Air Force Medical Center PLA China

ISBN: (纸本)9781450397056

Point cloud data is a collection of massive points containing the spatial position of each point on the target surface, which contains abundant spatial information. At present, it is also applied to the digital modeling of human surface in medical imaging, as the data basis for subsequent human body measurement, morphology estimation and data analysis. Among them, the key points is defined as the landmark position of the surface morphology analysis, those key points provides a reference position for the analysis work, and also reflects the symmetry of the body to a certain extent and morphology information. Aiming at the back shape analysis in clinical diagnosis, this paper proposes a two-stage key points positioning scheme of coarse segmentation and fine positioning. We design and build an pointwise artificial neural network to roughly locate the body part, in this part, we propose a maximum pooling module based on spatial location coding to express local features more strongly. Farther, we propose a gray distance and curvature based operator to match the position of key points. The experiment, shows that our method can effectively enhance the distinctiveness of features and meanwhile, reduce the influence from background.

关键词： Part Segmentation Deep Learning Point Cloud pattern recognition

来源：评论

学校读者我要写书评

暂无评论

An In-Depth Investigation of Cyber-Attack and Cyber Security: Emerging Trends and Current Events

An In-Depth Investigation of Cyber-Attack and Cyber Security...

引用

international conference on Circuits, Communication, Control and computing

作者： Chinmay Anand Shreya Korada S Raksha Dept. Computer Science and Engineering New Horizon College of Engineering (VTU) Bengaluru India Dept. name of organization New Horizon College of Engineering (VTU) Bengaluru India

The intricacy and originality of harmful software (also known as malware) have grown with time, despite the fact that it has existed since the invention of computers. The term “malware” (or “malicious code”) refers to software that carries out an attacker's malicious intent. Finding out how a piece of malware behaves and what it's likely to be used for is called malware analysis (such as Trojans horse, worms and virus). Malware may be identified and categorized into recognized families by exploiting its behavior and any patterns that follow it, whether they are static or dynamic. This survey study will give an outline of the methods for examining and categorizing the malware.

关键词： Technological innovation Computer viruses Market research Malware Safety pattern recognition Trojan horses

来源：评论

学校读者我要写书评

暂无评论

Network Attack Detection in the PfSense Firewall via Deep Learning

Network Attack Detection in the PfSense Firewall via Deep Le...

引用

Mechatronic Systems Supervision (IW_MSS), IEEE international Workshop on

作者： Merzoug Soltane Aimen Gasmi Laboratory of vision and intelligence (LAVIA) Echahid Cheikh Larbi Tebessi University Tebessa Algeria Department of Mathematics and Computer Science Echahid Cheikh Larbi Tebessi University Tebessa Algeria

ISBN: (数字)9798350378382

ISBN: (纸本)9798350378399

The detection of network attacks is a crucial aspect in ensuring the sustainability and proper functioning of information systems. Complex threat patterns and malicious actors possess the ability to inflict significant damage to cyber systems. In this study, we propose novel approaches utilizing deep learning techniques to identify and respond to threats and alerts found within network logs acquired through pfSense, an open-source firewall software. pfSense incorporates various robust security services including firewall capabilities, URL filtering, and virtual private networking (VPN), among others. The primary objective of this research is to analyze the acquired logs from a local installation of pfSense software, in order to develop a potent and efficient solution that can effectively manage traffic flow by automatically recognizing patterns through the proposed deep learning architectures, which present a significant challenge. To accomplish this, we have devised an attack detection system based on the CICDDOS2019 dataset, leveraging a deep neural network (DNN) model that has been seamlessly integrated into pfSense, enabling automatic identification and prevention of attacks.

关键词： Deep learning Uniform resource locators Firewalls (computing) Prevention and mitigation Artificial neural networks Network security software Virtual private networks pattern recognition Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Adaptive Scaling for Archival Table Structure recognition 16th

Adaptive Scaling for Archival Table Structure Recognition

引用

16th IAPR international conference on Document Analysis and recognition (ICDAR)

作者： Li, Xiao-Hui Yin, Fei Zhang, Xu-Yao Liu, Cheng-Lin Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit 95 Zhongguancun East Rd Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing Peoples R China

ISBN: (纸本)9783030865498

Table detection and structure recognition from archival document images remain challenging due to diverse table structures, complex document layouts, degraded image qualities and inconsistent table scales. In this paper, we propose an instance segmentation based approach for archival table structure recognition which utilizes both foreground cell content and background ruling line information. To overcome the influence from inconsistent table scales, we design an adaptive image scaling method based on average cell size and density of ruling lines inside each document image. Different from previous multi-scale training and testing approaches which usually slow down the speed of the whole system, our adaptive scaling resizes each image to a single optimal size which can not only improve overall model performance but also reduce memory and computing overhead on average. Extensive experiments on cTDaR 2019 Archival dataset show that our method can outperform the baselines and achieve new state-of-the-art performance, which demonstrates the effectiveness and superiority of the proposed method.

关键词： Archival document Table detection Table structure recognition Adaptive scaling

来源：评论

学校读者我要写书评

暂无评论

Revisiting the Benefits of Knowledge Distillation against Adversarial Examples

Revisiting the Benefits of Knowledge Distillation against Ad...

引用

Data Science and Information Technology (DSIT), international conference on

作者： Jiawen Li Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

Deep neural networks (DNNs) have always been a popular base model in many image classification tasks. However, some recent works suggest that there are some man made images will easily lead DNNs give wrong predictions. These images are generated by adding some invisible perturbations into clean images, which are the so-called adversarial examples. Since they are almost similar to original data but can fool DNNs, adversarial examples can bring the insecurity to many life-critical applications. Adversarial knowledge distillation is a positive defense method to attach improved robustness to the target DNNs against adversarial examples. In distillation, student models are trained by soft labels coming from robust pre-trained teacher networks. However, it is hard for researchers to ensure that supervised information comes from a better teacher model. In this paper, We focus on four potential factors of the teacher that may have an effect to the distillation performance of student model, and investigate whether and when they can boost the model robustness against adversarial attacks. Multiple quantitative experiment illustrate that these factors have impact on the distillation process and these results can be considered to choose a better teacher model. Further studies can focus on the combination of adversarial knowledge distillation and other defense schemes. Empirical results in this paper may also help select proper teacher in new complex distillation tasks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Knowledge Modeling of power grid regulation based on reasoning map

Knowledge Modeling of power grid regulation based on reasoni...

引用

2021 international conference on Energy, Power and Electrical Engineering, EPEE 2021

作者： Yang, Yang Huang, Yifan College of Electrical Engineering and Automation Fuzhou University Fujian Fuzhou China

To contribute to the intelligence and knowledge of power grid regulation and control operations, this paper presents a method of power grid regulation knowledge modeling based on ELG (Event Logic Graph), which includes an event word extraction based on a predicate-argument model, an event chain extraction and fusion based on event similarity theory, an event generalization based on a soft-pattern algorithm, and an event relationship recognition based on rule pattern matching method and joint constraints. Finally, this paper uses events as nodes and event relationships as directed edges to construct an affair graph stipulated by the power grid regulation and control regulations. The ELG is also called the new generation knowledge graph. But the knowledge graph can only describe the existence of entities and the upper and lower associations between entities. ELG can explain the inheritance, causality between entities and the logic of affair evolution, and the probability of transition between legacy and causality. Therefore, knowledge modeling based on ELG has intelligent advantages. Also, compared with ontology-based knowledge modeling methods, the method proposed in this paper can realize the dynamic representation of control operation knowledge, can express the logic of behavior and logic of operation, and also has higher retrieval accuracy. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： pattern matching

来源：评论

学校读者我要写书评

暂无评论

Exploration of pattern recognition Methods for Motor Imagery EEG Signal with Convolutional Neural Network Approach 3

Exploration of Pattern Recognition Methods for Motor Imagery...

引用

3rd international conference on Emerging Electrical Energy, Electronics and computing Technologies 2021, ICE4CT 2021

作者： Zahra, Hanina N Zakaria, Hasballah Hermanto, Beni R School of Electrical Engineering and Informatics Bandung Institute of Technology West Java Bandung40132 Indonesia

As an application of EEG, Motor Imagery based Brain-Computer Interface (MI BCI) plays a significant role in assisting patients with disability to communicate with their environment. MI BCI could now be realized through various methods such as machine learning. Many attempts using different machine learning approaches as MI BCI applications have been done with every one of them yielding various results. While some attempts managed to achieve agreeable results, some still failed. This failure may be caused by the separation of the feature extraction and classification steps, as this may lead to the loss of information which in turn causes lower classification accuracy. This problem can be solved by integrating feature extraction and classification by harnessing a classification algorithm that processed the input data as a whole until it produces the prediction, hence the use of convolutional neural network (CNN) approach which is known for its versatility in processing and classifying data all in one go. In this study, the CNN exploration involved a task to classify 5 different classes of fingers' imaginary movement (thumb, index, middle, ring, and pinky) based on the processed raw signal provided. The CNN performance was observed for both non-augmented and augmented data with the data augmentation techniques used include sliding window, noise addition, and the combination of those two methods. From these experiments, the results show that the CNN model managed to achieve an averaged accuracy of 47%, meanwhile with the help of augmentation techniques of sliding window, noise addition, and the combined methods, the model achieved even higher averaged accuracy of 57,1%, 47,2%, and 57,5% respectively. © Published under licence by IOP Publishing Ltd.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis from Sound Spectrograms via soft BoVW and Temporal Structure Modelling 9th

Sentiment Analysis from Sound Spectrograms via Soft BoVW and...

引用

9th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Pikramenos, George Smyrnis, Georgios Vernikos, Ioanrtis Konidaris, Thomas Spyrou, Evaggelos Perantonis, Stavros Natl Kapodistrian Univ Athens Dept Informat & Telecommun Athens Greece Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece Univ Thessaly Dept Comp Sci & Telecommun Lamia Greece NSCR Demokritos Inst Informat & Telecommun Athens Greece

ISBN: (纸本)9789897583971

Monitoring and analysis of human sentiments is currently one of the hottest research topics in the field of human-computer interaction, having many applications. However, in order to become practical in daily life, sentiment recognition techniques should analyze data collected in an unobtrusive way. For this reason, analyzing audio signals of human speech (as opposed to say biometrics) is considered key to potential emotion recognition systems. In this work, we expand upon previous efforts to analyze speech signals using computer vision techniques on their spectrograms. In particular, we utilize ORB descriptors on keypoints distributed on a regular grid over the spectrogram to obtain an intermediate representation. Firstly, a technique similar to Bag-of-Visual-Words (BoVW) is used, where a visual vocabulary is created by clustering keypoint descriptors, but instead a soft candidacy score is used to construct the histogram descriptors of the signal. Furthermore, a technique which takes into account the temporal structure of the spectrograms is examined, allowing for effective model regularization. Both of these techniques are evaluated in several popular emotion recognition datasets, with results indicating an improvement over the simple BoVW method.

关键词： Sentiment Analysis Speech Analysis Bag-of-Visual-Words

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Models for Predictive Marketing Analytics

Machine Learning Models for Predictive Marketing Analytics

引用

international conference on Computational and Characterization Techniques in Engineering & Sciences (CCTES)

作者： R. Satheeskumar Er. Vandana Dutt Ch. Srinivasa Reddy Zatin Gupta Sundarapandiyan Natarajan Muralidhar L B Computer Science and Engineering Narasaraopeta Engineering College JNTUK University Narasaraopet Andhra Pradesh GNA University Hoshiarpur Punjab Department of Information Technology Vignan’s Institute of Information Technology (A) Visakhapatnam Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida Uttar Pradesh Department of Management Studies Adithya Institute of Technology Coimbatore India Department of BMS School of Commerce JAIN (Deemed to be University) Bangalore

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

The objective of this study is to perform an investigation into the utilization of machine literacy models within the framework of prophetic marketing analytics. Because they make use of vast amounts of consumer data, machine literacy algorithms can recognise patterns and trends that traditional statistical approaches would be unable to recognise. This study investigates several different machine literacy approaches, including retrogression analysis, decision trees, and neural networks, to read client motions and preferences. Examples of these techniques include. It is important to concentrate attention on the sensitive character of the model, as well as its interpretability and its connection to the real world. The results of the inquiry demonstrate how improved marketing strategies may be achieved through the utilization of these advanced models, which offer a practical perspective. The result of this is that it can eventually lead to improved client targeting, marketing juggernauts that are substantiated, and an improvement in return on investment. The purpose of this article is to make a contribution to the growing body of knowledge in the field of predictive analytics by giving an in-depth assessment of how machine literacy has the potential to alter marketing processes by making them more data-driven and efficient.

关键词： Analytical models Adaptation models soft sensors Neural networks Predictive models Market research Data models Real-time systems pattern recognition Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Development of Neural Interface-Based Brain-Controlled Robotic Prosthetics for Enhanced Mobility in Amputees

Development of Neural Interface-Based Brain-Controlled Robot...

引用

Emerging Smart computing and Informatics (ESCI), conference on

作者： Manisha Veer Pradnya Borkar Rohan Phatak Kirti H. Wanjale Shirish Inamdar Saurabh Bhattacharya Department of Pharmaceutical Chemistry Krishna Institute of Pharmacy Krishna Institute of Pharmacy Krishna Vishwa Vidyapeeth "Deemed to be University" Maharashtra India Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Pharmacogonsy Krishna Institute of Pharmacy Krishna Institute of Pharmacy Krishna Vishwa Vidyapeeth "Deemed to be University" Karad Maharashtra India Vishwakarma Institute of Technology Pune Department of Pharmacy Practice Krishna Institute of Pharmacy Krishna Institute of Pharmacy Krishna Vishwa Vidyapeeth "Deemed to be University" Karad Maharashtra India School of Computer Science & Engg. Galgotias University Greater Noida UP India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Brain-controlled robotic devices made possible by neural interfaces are a hopeful new way to help amputees recover, as they give them more freedom and a better quality of life. Traditional prosthetics don't always offer real-time, natural control, which makes them frustrating to use and limits their abilities. This essay talks about how important it is to have prostheses that can work with the user's brain so that replacing limbs feels more normal and works better. Our goal is to create and test a neural interface technology that lets robotic replacement limbs be controlled directly from the brain. One of the ways used is creating a machine learning system to understand neural signals obtained through noninvasive electroencephalography (EEG), and these signals are then combined with a cutting-edge robotic limb. We used complex signal processing and pattern recognition techniques to figure out what the user was trying to do and make the prosthetic arm move precisely. Our system can correctly figure out different moving intents with little to no delay, according to the results. Preliminary tests with amputees showed that the new prostheses made it much easier and faster to do different jobs compared to standard ones. Participants said they were happier and more comfortable, which shows that this technology could change how prosthetics are controlled. This study lays the groundwork for future research on brain-controlled artificial systems that are scalable and easy for anyone to use. These systems could greatly assist amputees all over the world.

关键词： Training Accuracy Machine learning Signal processing Electroencephalography Real-time systems Delays Robots Standards Prosthetics

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 << < 99 100 101 102 103 104 105 106 107 108 > >>

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：