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

6,797 篇 会议
647 册 图书
127 篇 期刊文献

馆藏范围

7,570 篇 电子文献
2 种 纸本馆藏

日期分布

学科分类号

3,892 篇 工学
- 3,084 篇 计算机科学与技术...
- 1,402 篇 软件工程
- 793 篇 电气工程
- 676 篇 信息与通信工程
- 502 篇 控制科学与工程
- 298 篇 生物工程
- 281 篇 生物医学工程（可授...
- 265 篇 机械工程
- 189 篇 光学工程
- 162 篇 电子科学与技术（可...
- 144 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
1,220 篇 理学
- 671 篇 数学
- 357 篇 物理学
- 333 篇 生物学
- 197 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
273 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
17 篇 经济学
5 篇 军事学

主题

3,167 篇 pattern recognit...
535 篇 feature extracti...
431 篇 artificial intel...
385 篇 neural networks
297 篇 machine learning
295 篇 data mining
233 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
182 篇 local binary pat...
168 篇 computational mo...
160 篇 computer vision
147 篇 computer applica...
147 篇 humans
147 篇 testing
143 篇 training

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

7,289 篇 英文
216 篇 其他
81 篇 中文

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

共 7572 条记录，以下是1331-1340 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：

Anomaly Detection of Distribution Network Synchronous Measurement Data Based on Large Dimensional Random Matrix 2nd

Anomaly Detection of Distribution Network Synchronous Measur...

引用

2nd international conference of Artificial Intelligence, Medical Engineering, Education (AIMEE)

作者： Chen, Zhongming Zhang, Yaoyu Qing, Chuan Liu, Jierong Tang, Jiaqi Pang, Jingzhi Guangdong Power Grid Co Ltd Foshan Power Supply Bur Foshan 528200 Guangdong Peoples R China

ISBN: (纸本)9783030120825;9783030120818

In order to identify faults of power system measurement subsystem, a method based on deep belief network is proposed in this paper. Firstly, data from actual measurement system is collected and divided into training and test samples. And then, the data is used to train a deep belief network. Finally, the model's fault diagnosis results and actual samples' labels are combined as a cross-validation set to test the deep belief network. The results show that the method based on deep belief network proposed in this paper can be more stable and reliable identification of electric power measurement equipment fault diagnosis.

关键词： Deep belief network Measurement equipment Fault diagnosis pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Fingerprinting User Privacy in Web Applications 2020

Fingerprinting User Privacy in Web Applications

引用

Proceedings of the 2020 9th international conference on computing and pattern recognition

作者： Xujing Huang Xiamen University of Technology Xiamen Fujian China

ISBN: (纸本)9781450387835

Information leakage by side channels in web applications is a major security threat, even when web traffic is encrypted. In this paper, we describe an automated system to analyse leakages of user privacy. Previous works focus on communications directly interacting with sensitive information. We show how, in real-world web applications, user information can be leaked through "non-intuitive" communications, which do not contain direct interactions with sensitive information. Unexpectedly, we found that user privacy can be leaked more from this kind of "non-intuitive" communication than direct interactions. This work also discloses user identities can be inferred by traffic analysis. In this work, we combine machine learning to recognize traffic pattern, i.e., Hidden Markov model is used to fingerprint web traffic of user privacy.

关键词： Information leakage user identity pattern recognition traffic analysis fingerprinting hidden markov model

来源：评论

学校读者我要写书评

暂无评论

software-Hardware Co-Optimization for CNNs Based on Reconfigurable Devices

Software-Hardware Co-Optimization for CNNs Based on Reconfig...

引用

IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Fang Liu Zimeng Fan Yanxiang He Min Peng School of Computer Science Wuhan University Wuhan City College Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China School of Computer Science Wuhan University Wuhan China

Convolutional Neural Network (CNN) is an efficient recognition algorithm used in pattern recognition, image processing, etc. The problem of how to build an efficient computational system for CNNs has become a pressing one, which is traditionally achieved by software optimization or hardware accelerator design. In contrast, this paper argues that software algorithms and hardware architectures affect each other in neural network applications with a high degree of coupling. In this paper, we propose a software and hardware-based co-optimization design to improve CNNs’ processing efficiency by co-optimization of software and hardware. First, a modular analysis and collaborative design are carried out for the ShuffleNetV2 model by implementing quantization and improving the computational unit. Second, the model is optimized based on reconfigurable computing devices for its characteristics. Third, 8 bit quantization is implemented, while the depth-separable convolution operation and channel selection module is redesigned to make the module perform operations in a hardware-friendly form. The experimental work was carried out on the FPGA platform Xilin xzynqxc-7Z045 using High Level Synthesis (HLS). The experimental results show that the optimized model has a significant improvement in terms of resource utilization and latency.

关键词： Quantization (signal) Convolution Computational modeling software algorithms software pattern recognition Resource management

来源：评论

学校读者我要写书评

暂无评论

Parallelized Sequential Indexing Tables for Fast High-Volume Data Processing

Parallelized Sequential Indexing Tables for Fast High-Volume...

引用

2020 international Instrumentation and Measurement Technology conference

作者： Tusor, Balazs Toth, Janos T. Varkonyi-Koczy, Armamari R. Obuda Univ Doctoral Sch Appl Informat & Appl Math Budapest Hungary J Selye Univ Dept Math & Informat Komarno Slovakia Obuda Univ Inst Automat Budapest Hungary

ISBN: (纸本)9781728144610;9781728144603

In the age of Big Data, processing high volumes of data as fast as possible is an important task. Parallel computing is a useful tool that has become more and more available and widespread in the past decade, making it possible to accelerate traditional data processing methods or create new ones that are built upon parallelization techniques. Sequential Fuzzy Indexing Tables are classifiers that expand the capabilities of Lookup Tables in order to achieve a fast classification. However, due to the size of their structure, they cannot be used for problems with larger complexity. In this paper, a new classifier architecture is proposed that uses parallelization techniques to be used in quick processing of large volumes of data.

关键词： signal processing big data pattern recognition parallel computing classification machine learning

来源：评论

学校读者我要写书评

暂无评论

Thwarting Cyber Crime and Phishing Attacks with Machine Learning: A Study

Thwarting Cyber Crime and Phishing Attacks with Machine Lear...

引用

international conference on Advanced computing and Communication Systems (ICACCS)

作者： M Arshey K S Angel Viji Noorul Islam Centre for Higher Education Thuckalay College of Engineering Kidangoor

Almost over 4 billion people are currently making rampant usage of the internet. The massive utilization of mobile technology along with the rise of the digital era caused a socio-technical threat to the Government and to the public. Many new developments in the internet and modern technologies give rise to new illegal and unethical opportunities among which some of them are crime. Cyber crime is an unlawful means which makes use of a digital media either as a tool or as a target or both. Cyber crime cases, which includes mainly the Phishing attacks and many other attacks in the prevailing COVID -19 situation, have reached an alarming rate with the outburst of numerous forms of crime. This paper focuses on various types of cyber crime and targets some of the present day cyber crime attacks based on Phishing, Artificial Intelligence, Cloud technology and Block chain. The principal objective of this work is to identify how Machine Learning can be deployed in detection of diversified fields of cyber crime. The application of various Machine Learning models in the prediction, identification and mitigation of complex threats is also discussed.

关键词： COVID-19 Phishing Machine learning Tools Predictive models pattern recognition Security

来源：评论

学校读者我要写书评

暂无评论

DEEP LEARNING FOR pattern recognition OF INTERHARMONICS IN TIME-SERIES AND SPECTROGRAMS

DEEP LEARNING FOR PATTERN RECOGNITION OF INTERHARMONICS IN T...

引用

CIRED 2021 - The 26th international conference and Exhibition on Electricity Distribution

作者： R. A. Oliveira V. Ravindran S. Rönnberg M. H. J. Bollen Electric Power Engineering Luleå Technical University Skellefteå Sweden

This work applies an unsupervised deep feature learning to finding patterns of interharmonics. The main objectives of this work are to provide an additional graphical tool to handle two distinct data inputs: (a) individual interharmonics components in time-series; (b) broadband spectrum by employing spectrograms. Both data inputs are analysed employing an autoencoder based on convolutional neural networks followed by clustering. The application of the method results in the most common patterns in time-series or spectrograms. Two study cases are presented by applying the method to measurements from solar installations in Finland and Sweden. The results show the usefulness of the method to recognize interharmonics in a single frequency and broadband spectrum.

关键词： unsupervised learning feature extraction deep learning (artificial intelligence) time series convolutional neural nets pattern clustering power engineering computing

来源：评论

学校读者我要写书评

暂无评论

A new Deep learning model for Sequential pattern Mining using Ensemble learning and Models selection Taking Mobile Activity recognition as a case 16

A new Deep learning model for Sequential Pattern Mining usin...

引用

16th international conference on Mobile Systems and Pervasive computing (MobiSPC) / 14th international conference on Future Networks and Communications (FNC) / 9th international conference on Sustainable Energy Information Technology

作者： Djellali, Choukri Adda, Mehdi Univ Quebec Rimouski Dept Comp Sci & Engn Rimouski PQ Canada

Sequential pattern mining has gained popularity in Data Mining and pattern recognition. Most sequential pattern mining algorithms are influenced by noisy variables, parameters tuning, bias-variance dilemma and learning instability. This paper presents a new deep learning model for sequential pattern mining, by using ensemble learning and models selection. Experimental studies on mobile activity recognition showed that our deep learning model, which is named Deep Sequential pattern Mining (abbreviated as DeepSPM), obtained an enhanced generalization in comparison with Long Short Term Memory (LSTM), Bidirectional Associative Memory (BAM) and Hopfield. We provide a comparative performance analysis of pattern recognition. The advantages and the drawbacks of the benchmarking models are critically discussed. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Data Mining pattern recognition Deep learning Categorization Artificial Neural Networks Models selection Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

A Proficient Model to Classify Bangladeshi Bank Notes for Automatic Vending Machine Using a Tiny Dataset with One-Shot Learning Siamese Networks 11

A Proficient Model to Classify Bangladeshi Bank Notes for Au...

引用

11th international conference on computing, Communication and Networking Technologies, ICCCNT 2020

作者： Hossain, Md. Ekram Islam, Arni Islam, Md. Sanzidul Daffodil International University Department of Software Engineering Dhaka Bangladesh Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781728168517

Automatic vending machine is a necessity at this technological era. It's a step to go toward the vendor-less shop management, which supports the commandment of the 4th Industrial Revolution. But image recognition system needs a lot of data to get the pattern. Deep learning applications is very computationally extravagant for getting good features and find in many cases that little data cannot give good learning features. We have used and reworked the architecture of Siamese Neural Network for One-shot learning to recognize the Bangladeshi bank notes with a tiny dataset. In this article we analyzed 20 images only for 5 different Bangladeshi bank notes what people used regularly. This research will help general people to get better experience with vending machines which can recognize notes with one data example only. We used 5 notes (5,10,20,50,100 TAKA) and get excellent result with 97.38% accuracy using help of convolutional architecture. © 2020 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Modified Quick Fuzzy Hypersphere Neural Network for pattern Classification Using Supervised Clustering 2nd

Modified Quick Fuzzy Hypersphere Neural Network for Pattern ...

引用

2nd international conference on soft computing and Signal Processing, ICSCSP 2019

作者： Mane, D.T. Kshirsagar, J.P. Kulkarni, U.V. Department of Computer Science & Engineering S. G. G. S. I. E. & T. NandedMaharashtra431606 India Department of Computer Engineering Rajarshi Shahu College of Engineering PuneMaharashtra411033 India

ISBN: (纸本)9789811524745

Defining methods which map the features present in the input to a binomial class output is the core objective of pattern classification. The Modified Quick Fuzzy Hypersphere Neural Network (MQFHSNN) algorithm proposed is an extension of the existing Class-Specific Fuzzy Hypersphere Neural Network (CSFHSNN). Its membership function has been modified such that it outperforms the existing algorithms in the field of pattern classification. Fuzzy set hyperspheres are employed by MQFHSNN for pattern clustering and classes are represented by a combination of fuzzy set hypersphere. By using class labels for forming the clusters, the presented model gives 100% accuracy on the training data. The core contributors to facilitate learning in MQFHSNN are: creation of hyperspheres based on measurements provided by interclass and intraclass distance techniques as well as decision of patterns of individual classes by the fuzzy membership function. The proposed model is put into test on four standard datasets and the results obtained are more superior to the existing models. This leads us to the conclusion that MQFHSNN is being used for improvising model accuracy in pattern classification. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Fuzzy sets

来源：评论

学校读者我要写书评

暂无评论

soft-wearable device for the estimation of shoulder orientation and gesture 12th

Soft-wearable device for the estimation of shoulder orientat...

引用

12th international conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020

作者： Contreras-González, Aldo F. Samper-Escudero, José Luis Pont-Esteban, David Sáez-Sáez, Francisco Javier Sánchez-Urán, Miguel Ángel Ferre, Manuel UPM-CSIC Universidad Politécnica de Madrid Madrid28006 Spain

ISBN: (纸本)9783030581466

This study presents the development of a wearable device that merges capacitive soft-flexion and surface electromyography (sEMG) sensors for the estimation of shoulder orientation and movement, evaluating five natural movement gestures of the human arm. The use of Time Series Networks (TSN) to estimate the arm orientation, and a pattern recognition method for the estimation of the classification of the gesture are proposed. It is demonstrated that it is possible to know the orientation of the shoulder, and that the algorithm is capable of recognising the five gestures proposed with two different configurations. The study is performed on people who reported healthy upper limbs. © The Author(s) 2020.

关键词： Wearable sensors

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 << < 130 131 132 133 134 135 136 137 138 139 > >>

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：