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 of Soft Computing and Pattern Recognition"

共 7589 条记录，以下是1481-1490 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：

Comparison of EMG signal classification algorithms for the control of an upper limb prosthesis prototype

Comparison of EMG signal classification algorithms for the c...

引用

international conference on Electrical Engineering, computing Science and Automatic Control (CCE)

作者： Daniel Lorias Espinoza Leobardo Elí Sánchez Velasco CINVESTAV IPN México City

ISBN: (数字)9781728189871

ISBN: (纸本)9781728189888

In this paper, Machine Learning algorithms (Decision Trees and Support Vector Machines) are proposed and compared to select a classification system for EMG signals to improve the performance of pattern recognition for the control of a prosthesis prototype. The training, validation and signal classification were made using the Classification Learner application of the MatLab software, using a database captured with the commercial myoelectric armband MYO which contain the information of eight different hand movements. The results show that Support Vector Machines algorithms have a better performance than the decision trees, reaching the 99.8% of accuracy with linear and quadratic kernel and the 99.9% using a cubic kernel.

关键词： Support vector machines Electromyography Classification algorithms Robots pattern recognition Machine learning algorithms Kernel

来源：评论

学校读者我要写书评

暂无评论

Arduino microcontroller based Cashline Security System based on vein recognition Using Dactylography Technology 3

Arduino microcontroller based Cashline Security System based...

引用

3rd international conference on computing Methodologies and Communication (ICCMC)

作者： Rubini, M. Kavisarathi, M. Kaviya, R. Shankarr, B. P. Kiruba Pavithra, A. Praveen, R. KS Rangasamy Coll Technol Dept Elect & Commun Engn Tiruchengode India

ISBN: (纸本)9781538678084

In recent times, Cashline Systems are highly used for most of the bank transactions. Cashline system security is becoming more and more important in all aspects. On other hand the ATM frauds such as Duplicating ATM cards and card skimming were increased. To overcome such frauds dactylography technology is used in the proposed system. The advantage of the dactylography technology results on an entirely card free transaction. Even for the identical twins, the finger vein pattern is matchless. The width of the vein may be changed due to temperature changes or blood pressure but the centre line become stable. Then the extracted line will be used for the future identification purpose. The cashline system is to increase authenticity, confidentiality as well as user trust towards ATM transaction. After the analyzation of finger vein of the authenticated person, the next step is followed by means of the analyzed one's finger vein matching with the recorded vein pattern of the related banks database. Then high security level GSM module will generate an OTP and sends it to the authorized users mobile then followed by entering the OTP to the ATM machine, the verification is done and then further transaction process is followed.

关键词： Dactylography finger vein pattern GSM OTP

来源：评论

学校读者我要写书评

暂无评论

Online Gaussian LDA for Unsupervised pattern Mining from Utility Usage Data 19

Online Gaussian LDA for Unsupervised Pattern Mining from Uti...

引用

19th IEEE international conference on Machine Learning and Applications, ICMLA 2020

作者： Mohamad, Saad Bouchachia, Abdelhamid Bournemouth University Department of Computing Poole United Kingdom

ISBN: (纸本)9781728184708

Non-intrusive load monitoring (NILM) aims at separating a whole-home energy signal into its appliance components. Such method can be harnessed to provide various services to better manage and control energy consumption (optimal planning and saving). NILM has been traditionally approached from signal processing and electrical engineering perspectives. Recently, machine learning has started to play an important role in NILM. While most work has focused on supervised algorithms, unsupervised approaches can be more interesting and of practical use in real case scenarios. Specifically, they do not require labelled training data to be acquired from individual appliances and the algorithm can be deployed to operate on the measured aggregate data directly. In this paper, we propose a fully unsupervised NILM framework based on Bayesian hierarchical mixture models. In particular, we develop a new method based on Gaussian Latent Dirichlet Allocation (GLDA) in order to extract global components that summarise the energy signal. These components provide a representation of the consumption patterns. Designed to cope with big data, our algorithm, unlike existing NILM ones, does not focus on appliance recognition. To handle this massive data, GLDA works online. Another novelty of this work compared to the existing NILM is that the data involves different utilities (e.g, electricity, water and gas) as well as some sensors measurements. Finally, we propose different evaluation methods to analyse the results which show that our algorithm finds useful patterns. © 2020 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Non-symmetry and Anti-packing pattern Representation Model in Visual Tracking 15th

Non-symmetry and Anti-packing Pattern Representation Model i...

引用

15th international conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th international conference on Harmony Search, soft computing and Applications, ICHSA 2019

作者： Zheng, Yunping Li, Ruijun Sarem, Mudar School of Computer Science and Engineering South China University of Technology GuangzhouGuangdong510006 China School of Software Engineering Huazhong University of Science and Technology WuhanHubei430074 China General Organization of Remote Sensing Damascus Syria

ISBN: (纸本)9783030325909

Based on the non-symmetry and anti-packing pattern representation model (NAM), we propose a new division model in object tracking, whose most important characteristic is asymmetry. For the target region, we divide it into homogeneous blocks of different sizes and irregular positions. Pixels in the same homogeneous block have similar values, so we can use mean value and area to represent the feature of this block. When tracking the object, the proposed algorithm updates the mean values of each block to adapt to the change of the object. The characteristics of the whole target consist of the feature information and the position information of each block. Compared with the traditional division models, the NAM has fewer divided blocks but more highlight target structure characteristics. The experimental results in this paper show that our proposed tracking algorithm based on the NAM is better than those based on the quadtree or the compression tracking (CT) in both accuracy and speed. © 2020, Springer Nature Switzerland AG.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

international conference on soft computing and Signal Processing, ICSCSP 2018

International Conference on Soft Computing and Signal Proces...

引用

international conference on soft computing and Signal Processing, ICSCSP 2018

ISBN: (纸本)9789811335990

The proceedings contain 78 papers. The special focus in this conference is on soft computing and Signal Processing. The topics include: Comparative analysis of clustering algorithms with heart disease datasets using data mining weka tool;A machine learning approach for web intrusion detection: MAMLS perspective;white blood cell classification using convolutional neural network;analysis of mobile environment for ensuring cyber-security in IoT-based digital forensics;payment security mechanism of intelligent mobile terminal;Hybrid neuro-fuzzy method for data analysis of brain activity using EEG signals;gait recognition using J48-based identification with knee joint movements;cyber intelligence alternatives to offset online sedition by in-website image analysis through webcrawler cyberforensics;deep convolutional neural network-based diabetic retinopathy detection in digital fundus images;analysis of early detection of emerging patterns from social media networks: A data mining techniques perspective;a framework for semantic annotation and mapping of sensor data streams based on multiple linear regression;Cyclostationarity analysis of GPS signals for spoofing detection;implementation of fingerprint-based authentication system using blockchain;NSGLTLBOLE: A modified non-dominated sorting TLBO technique using group learning and learning experience of others for multi-objective test problems;homomorphic encryption scheme for data security in cloud using compression technique;efficient query clustering technique and context well-informed document clustering;motif shape primitives on fibonacci weighted neighborhood pattern for age classification;a novel virtual tunneling protocol for underwater wireless sensor networks;garbage monitoring system using internet of things;mobile learning recommender system based on learning styles;initial centroids for K-means using nearest neighbors and feature means.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of an Improved Focal Loss in Vehicle Detection 19th

Application of an Improved Focal Loss in Vehicle Detection

引用

19th international conference on Artificial Intelligence and soft computing, ICAISC 2020

作者： He, Xuanlin Yang, Jie Kasabov, Nikola Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Auckland University of Technology Auckland New Zealand

ISBN: (纸本)9783030614003

Object detection is an important and fundamental task in computer vision. Recently, the emergence of deep neural network has made considerable progress in object detection. Deep neural network object detectors can be grouped in two broad categories: the two-stage detector and the one-stage detector. One-stage detectors are faster than two-stage detectors. However, they suffer from a severe foreground-backg-round class imbalance during training that causes a low accuracy performance. RetinaNet is a one-stage detector with a novel loss function named Focal Loss which can reduce the class imbalance effect. Thereby RetinaNet outperforms all the two-stage and one-stage detectors in term of accuracy. The main idea of focal loss is to add a modulating factor to rectify the cross-entropy loss, which down-weights the loss of easy examples during training and thus focuses on the hard examples. However, cross-entropy loss only focuses on the loss of the ground-truth classes and thus it can’t gain the loss feedback from the false classes. Thereby cross-entropy loss does not achieve the best convergence. In this paper, we proposed a new loss function named Dual Cross-Entropy Focal Loss, which improves on the focal loss. Dual cross-entropy focal loss adds a modulating factor to rectify the dual cross-entropy loss towards focusing on the hard samples. Dual cross-entropy loss is an improved variant of cross-entropy loss, which gains the loss feedback from both the ground-truth classes and the false classes. We changed the loss function of RetinaNet from focal loss to our dual cross-entropy focal loss and performed some experiments on a small vehicle dataset. The experimental results show that our new loss function improves the vehicle detection performance. © 2020, Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

international conference on soft computing and Signal Processing, ICSCSP 2018

International Conference on Soft Computing and Signal Proces...

引用

international conference on soft computing and Signal Processing, ICSCSP 2018

ISBN: (纸本)9789811333927

The proceedings contain 156 papers. The special focus in this conference is on soft computing and Signal Processing. The topics include: Comparative analysis of clustering algorithms with heart disease datasets using data mining weka tool;A machine learning approach for web intrusion detection: MAMLS perspective;white blood cell classification using convolutional neural network;analysis of mobile environment for ensuring cyber-security in IoT-based digital forensics;payment security mechanism of intelligent mobile terminal;Hybrid neuro-fuzzy method for data analysis of brain activity using EEG signals;gait recognition using J48-based identification with knee joint movements;cyber intelligence alternatives to offset online sedition by in-website image analysis through webcrawler cyberforensics;deep convolutional neural network-based diabetic retinopathy detection in digital fundus images;analysis of early detection of emerging patterns from social media networks: A data mining techniques perspective;a framework for semantic annotation and mapping of sensor data streams based on multiple linear regression;Cyclostationarity analysis of GPS signals for spoofing detection;implementation of fingerprint-based authentication system using blockchain;NSGLTLBOLE: A modified non-dominated sorting TLBO technique using group learning and learning experience of others for multi-objective test problems;homomorphic encryption scheme for data security in cloud using compression technique;efficient query clustering technique and context well-informed document clustering;motif shape primitives on fibonacci weighted neighborhood pattern for age classification;a novel virtual tunneling protocol for underwater wireless sensor networks;garbage monitoring system using internet of things;mobile learning recommender system based on learning styles;initial centroids for K-means using nearest neighbors and feature means.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Visual Capability Estimation Using Motor Action pattern

Visual Capability Estimation Using Motor Action Pattern

引用

AHFE international conference on Human Factors and Systems Interaction

作者： Lu, Yanyu Ding, Lu Fu, Shan Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn 800 Dongchuan Rd Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Aeronut & Astronaut 800 Dongchuan Rd Shanghai Peoples R China

ISBN: (纸本)9783319943343;9783319943336

Visual channel is a very import input for human recognition during complex tasks. The critical challenge is to tell exactly how well the visual capability of a subjects in real time dynamically. In this research, we assume that the visual capability of a subject varies according to the real task situation, and that the performance of the subject on the task is a very important measurement for estimation of the visual capability of the subject. We use the motor action pattern as the indicator to investigate the level of visual capability of the subjects in relation to the characteristics of the visual information, the nature of the task and state of the subject in a simulated task environment. The research found there was a strong indication that variation of the visual capability was related to the nature of the task and the state of the subject. The motor action pattern was good indicator for visual capability.

关键词： Visual capability Motor action pattern recognition state

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep Learning Approach For Face Spoofing Detection

Hybrid Deep Learning Approach For Face Spoofing Detection

引用

international conference on Intelligent computing and Control Systems (ICCS)

作者： Shilpa, S. Sajeena, A. TKM Coll Engn Dept ECE Kollam Kerala India

ISBN: (数字)9781538681138

ISBN: (纸本)9781538681138

For access control in different applications and in their authentication, Face recognition plays a vital role replacing the traditional password methods. To accurately simulate the details of physical and physiological users, crime experts are developing techniques;these are known as spoofing attacks. Along with the traditional biometric techniques robust counter measures should be introduced to prevent such thefts. For the work, deep features are extracted from the image with the help of the modified CNN (Wavelet CNN). A stacked auto encoder is introduced for spatiality reduction. Along with the hybridisation, type of spoof attack is also detected in terms of printed attack or camera attack. In order to increase the detection rate, a score based prediction is also performed presenting accurate results in finding the type of attack.

关键词： Face recognition Local Binary pattern (LBP) Stacked Auto encoder Wavelet Convolutional Neural Networks (modified CNN) Spoofing Detection

来源：评论

学校读者我要写书评

暂无评论

Adoption of Smart Grid in Ghana Using pattern recognition Neural Networks

Adoption of Smart Grid in Ghana Using Pattern Recognition Ne...

引用

international conference on computing, Computational Modelling and Applications (ICCMA)

作者： Abubakar, Ruhiya Effah, Emmanuel K. Frimpong, Samuel Akwasi Acakpovi, Amevi Acheampong, Patrick Kadambi, Govind R. Kumar, K. M. Sharath Ghana Technol Univ Coll Fac Engn Dept Elect & Elect Engn Accra Ghana Ramaiah Univ Appl Sci Fac Engn Dept Elect & Elect Engn Bengaluru India Ghana Technol Univ Coll Fac Engn Dept Comp Engn Accra Ghana Accra Tech Univ Dept Elect Engn Accra Ghana Ghana Technol Univ Coll Fac Comp & Informat Technol Accra Ghana Ramaiah Sch Adv Studies Dept Comp Engn MS Bangalore Karnataka India

ISBN: (数字)9781728108186

ISBN: (纸本)9781728108186

Deployment of Smart Grid is neither a goal nor a destination, but rather an enabler to the provision of reliable, secured and clean electricity for the end- user or consumer. Overall Smart Grid vision is very well explained with the future of electricity systems, which largely depends on digitization and automation of the overall electricity value-chain, by enhancing electric power information to bi-directional flow and the provision of services that can support the operations of the generation, distribution and end-user usage of power can lead to improvement of electric power system efficiency. This work aims at analyzing factors and forecast effects on the adoption of Smart Grid in Ghana using pattern recognition Neural Net. The Primary data was collected using structured questionnaire and the questions were designed to test the perception of consumers on the deployment of Smart Grid. Also, the target group of respondents covered 80% of the regions in Ghana. Based on the collected data, the pattern recognition neural networks was employed in the analysis of data. Results indicated that education, government policy, cost and safety were the main drivers to the deployment of Smart Grid in Ghana. Other drivers like culture and societal perception recorded as insignificant variables to the deployment of distributed generation in Ghana. It is recommended that further research work should examine the extent of infrastructural preparedness of Ghana for the deployment of Smart Grid.

关键词： Smart Grid pattern recognition Neural Network forecast adoption

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 << < 145 146 147 148 149 150 151 152 153 154 > >>

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：