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

1,646 篇 会议
14 册 图书
11 篇 期刊文献

馆藏范围

1,671 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,182 篇 工学
- 901 篇 计算机科学与技术...
- 598 篇 软件工程
- 324 篇 光学工程
- 279 篇 信息与通信工程
- 258 篇 电气工程
- 174 篇 生物工程
- 153 篇 控制科学与工程
- 122 篇 机械工程
- 108 篇 生物医学工程（可授...
- 57 篇 电子科学与技术（可...
- 48 篇 化学工程与技术
- 48 篇 安全科学与工程
- 47 篇 材料科学与工程（可...
- 38 篇 仪器科学与技术
- 37 篇 交通运输工程
- 26 篇 建筑学
- 25 篇 土木工程
556 篇 理学
- 352 篇 物理学
- 200 篇 数学
- 176 篇 生物学
- 63 篇 化学
- 57 篇 统计学（可授理学、...
213 篇 医学
- 202 篇 临床医学
- 61 篇 基础医学(可授医学...
- 45 篇 药学(可授医学、理...
- 24 篇 公共卫生与预防医...
175 篇 管理学
- 97 篇 管理科学与工程(可...
- 80 篇 图书情报与档案管...
- 31 篇 工商管理
28 篇 农学
- 28 篇 作物学
19 篇 法学
17 篇 经济学
8 篇 教育学
5 篇 军事学
1 篇 文学

主题

307 篇 computer vision
228 篇 image processing
105 篇 image segmentati...
92 篇 feature extracti...
76 篇 deep learning
50 篇 object detection
42 篇 cameras
39 篇 image edge detec...
37 篇 convolutional ne...
34 篇 visualization
34 篇 image recognitio...
32 篇 machine learning
32 篇 image reconstruc...
31 篇 neural networks
30 篇 image color anal...
28 篇 computational mo...
28 篇 shape
28 篇 training
26 篇 image analysis
25 篇 image enhancemen...

机构

6 篇 university of ch...
5 篇 comput & inf sci...
5 篇 department of co...
4 篇 chitkara univers...
4 篇 image processing...
4 篇 beijing institut...
4 篇 college of compu...
3 篇 shanghai jiao to...
3 篇 dept of electr &...
3 篇 south china univ...
3 篇 inria sophia-ant...
3 篇 school of comput...
3 篇 department of ma...
3 篇 shenyang institu...
3 篇 department of co...
3 篇 school of electr...
3 篇 school of comput...
3 篇 college of compu...
3 篇 dept of control ...
3 篇 department of in...

作者

6 篇 andayani u.
5 篇 syahputra m.f.
5 篇 mohana
5 篇 siregar b.
4 篇 yang yang
4 篇 wang wei
4 篇 hassan ghassemia...
4 篇 li hui
4 篇 shohreh kasaei
4 篇 e.j. delp
3 篇 luo haibo
3 篇 paul joseph sure...
3 篇 wang qian
3 篇 ying liu
3 篇 maryam imani
3 篇 saurav sumeet
3 篇 weickert joachim
3 篇 muchtar m.a.
3 篇 xin wang
3 篇 aggarwal j.k.

语言

1,500 篇 英文
165 篇 其他
13 篇 中文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1671 条记录，以下是1101-1110 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：

Tiny Electronic Component Detection Based on Deep Learning

Tiny Electronic Component Detection Based on Deep Learning

引用

international conference on Cloud Computing and Internet of Things (CCIOT)

作者： Chun Liu Shaoqian Liu School of Computer HuBei University of Technology Wuhan China

ISBN: (数字)9781538671412

ISBN: (纸本)9781538671429

Tiny electronic component detection mostly suffers from compact size and multiple interferences of environment. To solve this problem, this paper presents an object detection method based on convolutional neural networks (CNNs). This method combines residual blocks in residual networks with CNNs. The CNNs can reduce the dimensions of the image, and the residual block in the residual network can train deeper neural networks, and then use the successful application of CNNs in computer vision to improve the recognition rate of components and improve the efficiency of automated processing of tiny electronic components. After the hyper-parameter adjustment, this method achieved 95.63% accuracy on our test set.

关键词： Convolution Feature extraction Training Resistance Convolutional neural networks Machine learning

来源：评论

学校读者我要写书评

暂无评论

Classification of the PolSAR Data Using Dual Classifiers

Classification of the PolSAR Data Using Dual Classifiers

引用

international conference on image, vision and Computing (ICIVC)

作者： Yan Duan Huili Duan Mingwei Sun Hubei Geomatics Information Center Wuhan China Yichang Surveying and Mapping Trade Society Yichang China School of Remote Sensing and Information Engineering Wuhan University Wuhan China

ISBN: (纸本)9781538649923

Classification of the polarimetric synthetic aperture radar (PolSAR) data is an important facet of synthetic aperture radar (SAR) image interpretation. In general, many polarimetric features can be extracted from PolSAR data. However, not all features are benefit for classification and too many polarimetric features result in the low classification efficiency. We introduce a method to deal with many polarimetric features and obtain both high classification accuracy and high classification efficiency. We first preprocess the PolSAR data to obtain objects, i.e., homogeneous regions. Next, we apply polarimetric feature processing to compute various polarimetric features of the PolSAR data. Based on the classification of the sample information, we then select the prominent polarimetric features using the data mining attributes of decision tree algorithm (DTA). Finally, we obtain classification results through the selected polarimetric features by DTA, the sample data and support vector machine (SVM). We verified the proposed method using the AirSAR L-Band PolSAR data. Our experiments indicate that the classification accuracy of the proposed method is equivalent to that of SVM and the computational efficiency is comparable to that of DTA. Thus, the proposed method integrates the advantages of both DTA and SVM.

关键词： Support vector machines image segmentation Filtering Speckle Synthetic aperture radar Classification algorithms Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A Rumor Events Detection Method Based on Deep Bidirectional GRU Neural Network

A Rumor Events Detection Method Based on Deep Bidirectional ...

引用

international conference on image, vision and Computing (ICIVC)

作者： Lizhao Li Guoyong Cai Nannan Chen School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781538649923

Traditional rumors detection methods often rely on statistical analysis to manually select features to construct classifiers. Not only is the message feature selection difficult, but the gap, between the representation space where the shallow statistical features of information exist and the representation space where the highly abstract features including semantics and emotion of information exist, is very big. Thus, the result of traditional classifiers based on the shallow or middle features is not so good. Due to this problem, a rumors deteciton method based on Deep Bidirectional Gated Recurrent Unit (D-Bi-GRU) is presented. To capture the evolution of group response information of microblog events over time, we consider the forward and backward sequences of microblog flow of group response information along time line simultaneously. The evolution representations of deep latent space including semantic and emotion learned by stack multi layers Bi-GRUs to rumor detection. Experimental results on a real world data set showed that rumor events detection by considering bidirectional sequence of group response information simultaneously can obtain a better performance, and stack multi-layers Bi-GRUs can better detect rumor events in microblog.

关键词： Feature extraction Neural networks Logic gates Event detection Probability distribution Semantics Training

来源：评论

学校读者我要写书评

暂无评论

Brazilian Republic Presidency Mobile Telephony Consumption Cost Reduction with Outliers Detection

Brazilian Republic Presidency Mobile Telephony Consumption C...

引用

international conference on image, vision and Computing (ICIVC)

作者： Rodrigo Hagstrom Ricardo Carvalho Rommel Carvalho Heitor Faria Tassio Melo Welder Luz Priscila Solis Department of Computer Science (CIC) University of Brasilia (UnB) Brasilia DF Brazil

ISBN: (纸本)9781538649923

After the Federal Court of Audit's decision on Judgment 1601/2005, the Brazilian Government has sought to reduce expenditure on telephone expenses. In this understanding, the Presidency of the Republic acquired Telecom Expense Management software, which proposes to provide telephone management, focusing on the efficiency in the use of resources and reducing the risk of having particular phone calls paid by the government. However, the software has not yet resulted in the volume of savings expected and required after the issuance of Decree 8.540/2015, which sets goals for reducing the consumption of resources with telephone expenses. The present paper studies the behavior of organization mobile phones of Brazilian Republic Presidency, in order to detect outliers through clustering processes as K-means, FarthestFirst and others, composed by calls registers with characteristics (time, duration and day of the week) that are not related to the corporation use. The results accused that 33 thousand calls were suspect of being private, about 10%, against 0.5% of previous solution and a confirmation that 90% of the suspicious calls obtained by the K-means method could be refunded in a sample presented to some employees of the Presidency of the Republic.

关键词： Software Risk management Telephone sets Standards Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Design of Industrial Robot Sorting System with Visual Guidance Based on Webots

Design of Industrial Robot Sorting System with Visual Guidan...

引用

international conference on computers, Communications, and Systems (ICCCS)

作者： Yunlong Pan Xing Ma Chunyang Mu Haiping An Jianyu Chen College of Electrical and Information Engineering North Minzu University Yinchuan China Institute of Information and Communication North Minzu University Yinchuan China College of Mechatronic Engineering North Minzu University Yinchuan China

ISBN: (纸本)9781538663516

Aiming at the low efficiency of artificial detection in industrial production line, this paper builds a simulation platform of visual guide sorting system based on Webots. For static target work pieces, image is captured by the camera, use Hu invariant moments quick recognition, and get the help of chain code to further identify, so that the sorting task can be done by robots. For dynamic target work pieces, it takes much time to process the image. There will be a tracking lag phenomenon. Using Kalman filter to predict the position, we can track the target. Experimental results showed that, with the feature in the centroid of shape and the tracking error in two pixels or less, the system could achieve target-detecting and tracking at the 0.2Sm/s speed of conveyor, as well as have a better robustness.

关键词： Cameras Sorting Robot vision systems Service robots Target tracking Shape

来源：评论

学校读者我要写书评

暂无评论

An efficient post-processing approach for dimensionality reduction methods for face recognition 3

An efficient post-processing approach for dimensionality red...

引用

3rd international conference on Advanced Technologies for Signal and image processing (ATSIP)

作者： Abbad, Abdelghafour Abbad, Khalid Tairi, Hamid Fac Sci Dhar EL Mahraz Lab LIIAN Fes Morocco Fac Sci & Technol Lab ISA Fes Morocco

ISBN: (纸本)9781538605516

In this paper we propose a new post-processing approach for dimensionality reduction methods based on multidimensional ensemble empirical mode decomposition (MEEMD). In the proposed method, the features are decomposed into different components and then we maximize the dependency and the dispersion between classes thanks to Gaussian filter and Butterworth filter. The performance of the proposed algorithm is demonstrated in experiments by several dimensionality reduction techniques on two public databases.

关键词： computer vision dimensionality reduction techniques face recognition MEEMD pattern recognition post-processing

来源：评论

学校读者我要写书评

暂无评论

Feature based Fruit Quality Grading System using Support Vector Machine

Feature based Fruit Quality Grading System using Support Vec...

引用

IEEE international conference on Recent Trends in Electronics, Information & Communication Technology

作者： Shweta S. Deulkar Sunita S. Barve IT Academy of Engineering Alandi Pune India

ISBN: (数字)9781538624401

ISBN: (纸本)9781538624418

The conventional post-harvesting process of horticultural fruit and vegetables is exorbitant and highly subjective which susceptible to errors. This process is extremely unreliable in terms of accuracy, throughput, speed and cost. An automated fruit grading approach is desirable to reduce the manual efforts and increase the efficiency. In this paper, we are developing a computer vision based an image acquisition and classification system for fruit grading. This system is divided into three modules image pre-processing, image segmentation and Classifier. In the first phase, we are extracting the image features such as image quality, area, perimeter, mean, variance, color, intensity. Next Otsu algorithm works on automatic threshold calculation and image binarization part. In the second phase k-means clustering is used for image segmentation. In last phase the vectors of color, intensity, segments, and image quality feature were utilized for training of the support vector machine structure. The image k-means clustering approach is embedded with support vector machine classifier to improve the speed and accuracy of the classifier. As a result, the system will be able to classify the fruit into three different categories. The proposed algorithm is implemented with an example of tomato fruit grading. The experiments consider real tomato image dataset of 200 samples.75% of the total dataset is used for training and remaining 25% used for testing purpose. Training dataset is distinguished into three categories depending on the maturity of tomato.

关键词： image color analysis Support vector machines Feature extraction Classification algorithms image segmentation Clustering algorithms Histograms

来源：评论

学校读者我要写书评

暂无评论

Preface

Communications in Computer and Information Science

引用

Communications in computer and Information Science 2019年 1019 CCIS卷 v页

作者： Arora, Chetan Mitra, Kaushik Department of Computer Science and Engineering Indian Institute of Technology Delhi New Delhi India Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

来源：评论

学校读者我要写书评

暂无评论

Maritime Target Detection and Tracking

Maritime Target Detection and Tracking

引用

2018 3rd international conference on computer Science and Information Engineering(ICCSIE 2018)

作者： Liu Jian Gao Wen Changchun University of Science and Technology Changchun Institute of Optics Fine Mechanics and PhysicsChinese Academy of Sciences

Method of object detection and tracking is one of hot topics in image processing and computer vision field,which is significant not only in military such as imaging guidance and military target tracking,but also for civil use such as security and monitoring and the intelligent man-machine *** marine targets,how to eliminate interference effectively and achieve accurate detection of moving targets is a key problem to be *** this paper,a method of image segmentation and line detection is proposed to detect the horizon,which can help to determine the area to be *** knowledge is used to detect the ship target in this *** identify the suspected ship,we detect it in multiple *** identifying the ship,the mean shift algorithm is applied to lock tracked *** experiment shows that the algorithm we proposed has good effect of detection and tracking for the ship target in the infrared image,and this algorithm has low computational complexity and small *** has been realized in the embedded hardware system and has high application value.

关键词： object tracking object detection line detection

来源：评论

学校读者我要写书评

暂无评论

Dynamic Hand Gesture Recognition Using computer vision and Neural Networks

Dynamic Hand Gesture Recognition Using Computer Vision and N...

引用

international conference for Convergence of Technology (I2CT)

作者： M. I. N. P. Munasinghe Department of Computer Science and Engineering University of Moratuwa Moratuwa Sri Lanka

Using hand gestures is one of the most natural ways of interacting with the computer and most importantly correct interpretation of moving hand gestures in real-time has many applications. In this paper, the author has designed and developed a system which can recognize gestures in front of a web camera real time using motion history images (MHI) and feedforward neural networks. Firstly, background from captured frames is removed using Gaussian mixture based background/foreground segmentation algorithm in order to capture moving areas in the frame and thereafter median filtering has applied to remove random noise from the frame. Then binary thresholding with Otsu's binarization has applied and it will identify optimal threshold value and these processed frames are merged and cumulative motion history image is generated using a developed algorithm based on the structural similarity measure. Structural similarity between the cumulated image and the initial frame also calculated and used in this algorithm. Finally feed forward neural network with stochastic gradient-based optimizer has used to classify the gestures.

关键词： Gesture recognition History Biological neural networks Feature extraction Real-time systems image segmentation Classification 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168页 << < 107 108 109 110 111 112 113 114 115 116 > >>

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：