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

6,459 篇 会议
966 篇 期刊文献
2 篇 学位论文
1 册 图书

馆藏范围

7,428 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,194 篇 工学
- 1,130 篇 电气工程
- 928 篇 计算机科学与技术...
- 667 篇 信息与通信工程
- 273 篇 控制科学与工程
- 204 篇 仪器科学与技术
- 165 篇 机械工程
- 165 篇 软件工程
- 128 篇 电子科学与技术（可...
- 101 篇 交通运输工程
- 101 篇 生物医学工程（可授...
- 90 篇 测绘科学与技术
- 72 篇 航空宇航科学与技...
- 34 篇 土木工程
- 29 篇 生物工程
- 24 篇 环境科学与工程（可...
- 20 篇 网络空间安全
- 17 篇 船舶与海洋工程
- 16 篇 光学工程
287 篇 理学
- 80 篇 系统科学
- 63 篇 物理学
- 50 篇 地球物理学
- 34 篇 数学
- 34 篇 生物学
- 24 篇 地理学
184 篇 医学
- 123 篇 临床医学
- 30 篇 基础医学(可授医学...
166 篇 管理学
- 156 篇 管理科学与工程(可...
49 篇 农学
- 26 篇 作物学
- 22 篇 农业资源与环境
35 篇 文学
- 35 篇 新闻传播学
14 篇 艺术学
6 篇 军事学
5 篇 经济学
4 篇 教育学
3 篇 法学

主题

7,428 篇 detection algori...
765 篇 feature extracti...
759 篇 detectors
620 篇 algorithm design...
582 篇 object detection
533 篇 image edge detec...
384 篇 testing
370 篇 robustness
331 篇 cameras
307 篇 computer science
291 篇 accuracy
284 篇 monitoring
276 篇 data mining
273 篇 computational mo...
255 篇 image segmentati...
236 篇 signal to noise ...
233 篇 clustering algor...
198 篇 change detection...
195 篇 pixel
191 篇 electrocardiogra...

机构

17 篇 school of electr...
15 篇 beijing universi...
13 篇 department of el...
13 篇 department of el...
11 篇 institute for in...
11 篇 department of el...
10 篇 national mobile ...
9 篇 department of el...
9 篇 wireless theorie...
8 篇 department of el...
8 篇 graduate school ...
8 篇 department of au...
8 篇 institute of com...
7 篇 beijing key labo...
7 篇 school of electr...
7 篇 department of el...
7 篇 department of el...
7 篇 department of el...
7 篇 mit lincoln labo...
7 篇 southeast univ n...

作者

13 篇 wei li
13 篇 bin wu
9 篇 dacheng yang
9 篇 ming chen
9 篇 h. wang
9 篇 r. raheli
8 篇 xin liu
8 篇 jaeseok kim
8 篇 shixin cheng
8 篇 keiichi tamura
8 篇 v.k. garg
8 篇 j. mcnames
8 篇 xin zhang
7 篇 lei wang
7 篇 a. schaum
7 篇 hajime kitakami
7 篇 hui zhao
7 篇 giulio colavolpe
7 篇 hui li
7 篇 yong li

语言

7,344 篇 英文
43 篇 其他
36 篇 中文
4 篇 西班牙文
1 篇 土耳其文

检索条件"主题词=detection algorithms"

共 7428 条记录，以下是1611-1620 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：

Disturbance Waveform detection Technology Based on Probability Density of Remaining Data

Disturbance Waveform Detection Technology Based on Probabili...

引用

IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Shan Jiang Jiabi Liang Ke Zhu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (数字)9781728190266

ISBN: (纸本)9781728190273

With the increasing application of disturbance waveform data, a general disturbance detection technology faced with various transient waveforms has practical significance for simplifying the detection process of specific disturbances and improving the accuracy of the specific disturbance detection. To this end, a detection algorithm for transient disturbance waveforms based on the probability density of remaining data is proposed in this paper. Firstly, the method of obtaining the remaining waveform data and its probability density is presented. Then, the probability distribution law of noise in power waveform data is studied based on the field measured data. Finally, according to the probability density difference of the remaining waveform data in adjacent periods, a transient waveform detection algorithm based on Wasserstein distance between probability densities is established. The threshold is determined by the box plot. A large amount of field measured data verifies the effectiveness of the proposed disturbance detection algorithm.

关键词： Renewable energy sources Power measurement Gaussian distribution Probability distribution Noise measurement Transient analysis detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Bayesian occupancy grid for active sonar detection and localization of moving targets

Bayesian occupancy grid for active sonar detection and local...

引用

OCEANS

作者： Karl Thomas Hjelmervik Kristoffer Engedal Andreassen Elin M Bohler Jorn Inge Vestgården Henrik Berg Dan Henrik S Stender Norwegian Defence Research Establishment (FFI)

ISBN: (数字)9781728154466

ISBN: (纸本)9781728184098

Active sonar performance is highly dependent on the surrounding environment. Conventional detection algorithms apply thresholds to acoustic data passed through a normalizer in order to detect targets. These methods fail to fully exploit available knowledge of the environment, which leads to higher false alarm rates than necessary, particularly in littoral environments. Furthermore, they do not exploit negative information, e.g. the significance of the repeated lack of threshold crossings in a given area. Sonar performance models may estimate both the probability of detection and false alarm in a known environment. Proper exploitation of this data allows for reduced false alarm rates in cluttering and reverberating environments. Furthermore, areas lacking threshold crossings and with high probability of detection, may be classified as target free. Bayesian occupancy grids is a probabilistic approach that takes into account both sensor information and prior information of surrounding walls or topography for localization of robots. Here we apply the method on synthetic sonar data combined with a sonar performance model. The synthetic sonar data contains moving and stationary targets in a littoral environment. The method's performance is compared to conventional algorithms, and its robustness to errors in the sound speed profile used in the modelling is assessed.

关键词： Location awareness Sonar Robot sensing systems Robustness Bayes methods detection algorithms Sonar detection

来源：评论

学校读者我要写书评

暂无评论

Identifying Social Networks of Programmers using Text Mining for Code Similarity detection

Identifying Social Networks of Programmers using Text Mining...

引用

International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Konstantinos F. Xylogiannopoulos Panagiotis Karampelas University of Calgary Calgary Canada Hellenic Air Force Academy Dekelia Greece

ISBN: (数字)9781728110561

ISBN: (纸本)9781728110578

The availability of code in many online repositories and collaborating platforms has posed new challenges in source code attribution not only for plagiarism detection but also in other settings such as in the use of insecure copied code in commercial application, etc. The sophistication of different type of attacks in the code sequence used especially by the students requires more effective code similarity detection algorithms. In this paper, a novel source code detection method is proposed that can identify programmers' social network based on advanced pattern detection text mining techniques. The proposed methodology has significant advantages against existing methods since ARPaD algorithm can detect all common patterns between all possible code sequences in one run. Therefore, the computational time is massively reduced to 0(mn log n). In order to assess the performance of the methodology, a new dataset was created by assigning to 46 students a code project with specific instructions. The assessment results have been visualized, producing the social network graphs of possible collaboration teams.

关键词： Text mining Visualization Social networking (online) Plagiarism Collaboration detection algorithms

来源：评论

学校读者我要写书评

暂无评论

ReCon: From the Bitstream to Piracy detection

ReCon: From the Bitstream to Piracy Detection

引用

Physical Assurance and Inspection of Electronics (PAINE), 2020 IEEE

作者： Grant Skipper Christopher Sozio Adam Duncan Andrew Lukefahr Martin Swany Intelligent Systems Engineering Indiana University Bloomington Indiana USA NAVSEA Crane Indiana USA

ISBN: (数字)9781728161211

ISBN: (纸本)9781728161228

Field-Programmable Gate Arrays (FPGAs) are used almost everywhere, from smart-phones to datacenters. FPGA functionality is determined by the intellectual property (IP) encoded within a vendor-proprietary binary configuration file, or bitstream, that is deployed on these devices. The potential value offered by IP creates many incentives for an adversary to attempt to steal it. The opaque nature of vendor bitstream formats has thus far limited the ability to detect stolen IP in deployed FPGAs. In this work we demonstrate the ability to detect instances of IP piracy given ONLY the FPGA configuration bitstream and a golden user netlist. While prior works have shown it is possible to reverse-engineer FPGA bitstreams into an underlying structural netlist, in isolation this netlist is of limited utility. We take this a step further by introducing ReCon, a tool to automatically assist in detecting pirated IP within a bitstream. ReCon first extracts a netlist from an unknown bitstream, then applies subgraph isomorphism algorithms to detect IP within the extracted netlist that are pirated from an original, or user, IP. Our experiments demonstrate ReCon as an effective method for piracy detection because it allows for a composite comparison between two bitstreams without needing to manually reverse engineer circuits and identify submodules.

关键词： Watermarking Intellectual property Tools Inspection IP networks detection algorithms Field programmable gate arrays

来源：评论

学校读者我要写书评

暂无评论

Robust QRS detection Using Combination of Three Independent Methods

Robust QRS Detection Using Combination of Three Independent ...

引用

Computers in Cardiology (CinC)

作者： Lukas Smital Lucie Marsanova Radovan Smisek Andrea Nemcova Martin Vitek Brno University of Technology Brno Czech Republic Institute of Scientific Instruments of the Czech Academy of Sciences Brno Czech Republic

ISBN: (数字)9781728173825

ISBN: (纸本)9781728111056

QRS detection is a fundamental step in ECG analysis. Although there are many algorithms reporting results close to 100%, this problem is still not resolved. The reported numbers are influenced by the quality of the detector, the quality of annotations and also by the chosen method of testing. In this study, we proposed and properly tested robust QRS detection algorithm based on a combination of three independent principles. For enhancement of QRS complexes there were developed three independent approaches based on continuous wavelet transform, Stockwell transform and phasor transform which are followed by individual adaptive thresholding. Each method produces candidates for QRS complexes which are further processed by cluster analysis resulting in final QRS positions. The proposed detection algorithm was tested on three complete standard ECG databases: MIT-BIH Arrhythmia Database, European ST-T Database and QT Database without any change in algorithm setting. We utilized complete data from mentioned databases including all provided leads and used original (not adjusted) reference positions of QRS complexes. Summarized detection accuracy for all three databases was expressed by sensitivity 99.16% and positive predictive value 98.99%.

关键词： Sensitivity Databases Detectors Electrocardiography detection algorithms Standards Testing

来源：评论

学校读者我要写书评

暂无评论

Failure Prediction in Datacenters Using Unsupervised Multimodal Anomaly detection

Failure Prediction in Datacenters Using Unsupervised Multimo...

引用

IEEE International Conference on Big Data

作者： Minglu Zhao Reo Furuhata Mulya Agung Hiroyuki Takizawa Tomoya Soma Graduate School of Information Sciences Tohoku University Cyberscience Center Tohoku University Corporate Business Development Division NEC Corporation

ISBN: (数字)9781728162515

ISBN: (纸本)9781728162522

Predicting hard drive failures in datacenters can help avoid wasting resources and waiting time for recovery. Anomaly detection from sensing data is commonly used for predicting failures. Usually, conventional threshold-based anomaly detection methods consider each sensor independently. However, deciding an optimal threshold for each type of sensors is not trivial, especially for large-scale systems in datacenters. To detect failures that cannot conventionally be detected, multimodal anomaly detection becomes crucial integrating sensing data from different types of sensors. This work proposes a correlation-based multimodal anomaly detection approach. This approach is applied to a Network-Attached Storage (NAS) system with multiple hard disk drives (HDDs) and three sensors, which are a thermal camera, a microphone, and system performance logs. The unimodal results show that the auditory and system performance model can detect temporal anomalies, and the thermal model can detect spatial anomalies. The multimodal results show that even with a simple filter and detection algorithms, the multimodal approach was able to detect failure signs before the real failure and also earlier than the auditory unimodal approach.

关键词： Temperature sensors Correlation System performance Filtering algorithms Big Data detection algorithms Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

detection of Spinal Fracture Lesions based on Improved Yolov2

Detection of Spinal Fracture Lesions based on Improved Yolov...

引用

IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)

作者： Gang Sha Junsheng Wu Bin Yu School of Computer Science Northwestern Polytechnical University Xi'an Xi'an Shaanxi China School of Software and Microelectronics Northwestern Polytechnical University Xi'an Xi'an Shaanxi China School of Computer Science and Technology Xidian University Xi'an Xi'an Shaanxi China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170060

Yolo algorithm has a good detection effect in target detection. Because of its high detection accuracy and fast detection speed, it is widely used in practice. Because of the problem that the complexity of spine CT images, the irregular shape of vertebral boundary, meanwhile there are artificial deviations and low efficiencies in clinic, which needs doctors' prior knowledge and clinical experience to determine lesions location in CT images, so it can not meet the clinical real-time needs. In this paper, We use deep learning to process the CT images of spine, and to detect and locate lesion of (cervical fracture, cfracture), (thoracic fracture, tfracture), (lumbar fracture, lfracture) by the improved YOLOv2. Through using lesions bounding box dimensional cluster and multiscale transformation of input CT images to improve detection efficiency and accuracy. The experiment shows the results are more accurate, and mAP (mean average precision) of detection algorithm is 75.30%, detection rate is 0.027 seconds per detection, and IOU((Intersection-over-Union) is 77.3, which can basically meet the clinical real-time needs.

关键词： Lesions Computed tomography Object detection Training Hospitals Machine learning detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Fall detection algorithm for the elderly based on human posture estimation

Fall detection algorithm for the elderly based on human post...

引用

Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Guangmin Sun Zhongqi Wang Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

With the acceleration of the global aging process, the safety and health of the elderly has become a widespread concern, and falls have become the main health threat of the elderly. In this paper, a fall detection model based on OpenPose human posture estimation algorithm is proposed by using the fall detection method based on machine vision. On the basis of OpenPose human key point detection, combined with SSD MobileNet object detection framework can remove the non human key points detected by OpenPose algorithm, reduce the false detection rate of the algorithm, improve the robustness of the algorithm in complex environment, and then extract the features of human joint points, use SVDD classification algorithm to classify, experiments show that this method can effectively detect the occurrence of falls, and the accuracy rate can reach more than 93%.

关键词： Human posture estimation OpenPose object detection Object detection falls aged person Human Posture Fall accuracy rate detection rate (DR) algorithms robot vision detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Rumor detection on Twitter Using Features Extraction Method

Rumor Detection on Twitter Using Features Extraction Method

引用

Information Technology To Enhance e-learning and Other Application (IT-ELA)

作者： Hussam Mohammed Jabir Mohammed Abdullah Naser Safaa O. Al-mamory University of Babylon Babylon Iraq College of Business Informatics University of Information Technology and Communications Baghdad Iraq

ISBN: (数字)9781728182339

ISBN: (纸本)9781728182346

Rumors can widely and rapidly diffuse in social networks than in offline platforms. This work was an attempt to address this challenge by introducing an approach for rumors detection, which learns from the Twitter dataset. In other words, this paper is going to suggest new features were extracted from Twitter datasets based on user behavior, the propagation features and the temporal features that representing the social context to reduce variation in features. Also, the proposed work involves adopting an ensemble classifier as a more appropriate approach and for achieving a better performance compared to existing individual-based classifiers. Moreover, the proposed method processes unbalanced data sets to reduce their impact on detection algorithms and improve the classification accuracy rate. Experimental results on the PHEME dataset showed that the new features made the classification process more effective and accurate compared to many related works of rumor classification that use the same data. Experimental results achieved 78.54% accuracy as an average of the events used.

关键词： Support vector machines Electronic learning Social networking (online) Blogs Feature extraction Information technology detection algorithms

来源：评论

学校读者我要写书评

暂无评论

High Precision detection Technology of Infrared Wall Cracks Based on Improved Single Shot Multibox Detector

High Precision Detection Technology of Infrared Wall Cracks ...

引用

Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： ZEHUA GAO YING LIU CHUWEN LAN School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

Building wall cracks seriously reduce the safety and stability of building structure. Aiming at the problems of slow speed, high cost and lack of objectivity of traditional crack detection technology, an infrared wall crack detection algorithm based on improved single shot multibox detector (SSD) is proposed in this paper. The algorithm combines infrared thermal imaging technology and improved SSD network to detect cracks in the infrared image of building wall model. The infrared thermal imaging technology can detect the cracks under the building coating or wallpaper. The improved SSD network optimizes the size and distribution of the prior box, and improves the recall rate of the network. The experimental data results show that the algorithm is effective and the detection accuracy is more than 98%, which has a certain practical value.

关键词： Training Buildings Thermal engineering Imaging Manuals Detectors detection algorithms

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 << < 158 159 160 161 162 163 164 165 166 167 > >>

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：