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

489 篇 会议
33 篇 期刊文献

馆藏范围

522 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

351 篇 工学
- 273 篇 信息与通信工程
- 137 篇 计算机科学与技术...
- 96 篇 软件工程
- 86 篇 电子科学与技术（可...
- 50 篇 航空宇航科学与技...
- 49 篇 控制科学与工程
- 41 篇 仪器科学与技术
- 38 篇 光学工程
- 27 篇 机械工程
- 20 篇 电气工程
- 20 篇 生物工程
- 19 篇 土木工程
- 17 篇 建筑学
- 16 篇 化学工程与技术
- 10 篇 环境科学与工程（可...
- 9 篇 测绘科学与技术
- 8 篇 安全科学与工程
- 6 篇 动力工程及工程热...
166 篇 理学
- 103 篇 数学
- 27 篇 统计学（可授理学、...
- 26 篇 生物学
- 24 篇 物理学
- 18 篇 化学
- 12 篇 大气科学
- 8 篇 地质学
- 8 篇 系统科学
41 篇 管理学
- 22 篇 管理科学与工程(可...
- 20 篇 图书情报与档案管...
13 篇 农学
- 8 篇 农业资源与环境
- 5 篇 作物学
11 篇 军事学
1 篇 经济学
1 篇 法学
1 篇 教育学

主题

89 篇 synthetic apertu...
22 篇 radar
22 篇 radar imaging
20 篇 feature extracti...
16 篇 object detection
15 篇 radar polarimetr...
15 篇 target recogniti...
15 篇 field programmab...
13 篇 training
12 篇 remote sensing
11 篇 sar
11 篇 accuracy
10 篇 convolutional ne...
9 篇 data processing
9 篇 signal to noise ...
9 篇 target tracking
9 篇 radar tracking
9 篇 convolution
9 篇 field programmab...
8 篇 imaging

机构

215 篇 beijing key labo...
147 篇 beijing key labo...
72 篇 radar research l...
61 篇 school of inform...
50 篇 beijing institut...
36 篇 advanced technol...
33 篇 beijing key labo...
25 篇 chongqing innova...
21 篇 radar technology...
19 篇 radar research l...
17 篇 beijing key labo...
17 篇 school of electr...
15 篇 school of inform...
13 篇 beijing key labo...
12 篇 beijing key labo...
11 篇 zhengzhou academ...
11 篇 shanghai institu...
10 篇 beijing institut...
9 篇 the advanced tec...
8 篇 school of inform...

作者

52 篇 ding zegang
40 篇 chen he
39 篇 he chen
35 篇 chen liang
33 篇 hu cheng
30 篇 wang yanhua
28 篇 liang chen
26 篇 xie yizhuang
26 篇 zegang ding
25 篇 li yang
25 篇 zeng tao
24 篇 cheng hu
24 篇 tao zeng
20 篇 linbo tang
20 篇 wang rui
19 篇 zhang liang
19 篇 yanhua wang
19 篇 tang linbo
18 篇 zhao baojun
17 篇 teng long

语言

503 篇 英文
16 篇 其他
3 篇 中文

检索条件"机构=BeijingKey Laboratory of Embedded Real-Time Information Processing Technology"

共 522 条记录，以下是261-270 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：

Airfield detection based on JPEG2000 compressed domain

Airfield detection based on JPEG2000 compressed domain

引用

IET International Radar Conference 2018, IRC 2018

作者： Duan, Chenhui Zhao, Baojun Tang, Linbo Li, Cheng Li, Chen Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Information Security Laboratory School of Information North China University of Technology Beijing100093 China

With the rapid increase of optical remote sensing (RS) images, on-orbit specific target detection has been facing more and more challenges: limited processing environment, wireless bandwidth, space, power and storage. To resolve this issue, visual characteristics in the compressed domain are exploited to represent and recognise specific objects. In this study, a new saliency method and an airfield detection framework in the JPEG2000 compressed domain is proposed. First, the authors exploit the header information in raw JPEG2000 code streams to generate structural saliency map, and a great deal of nonstructural regions in RS images are eliminated. Second, airfield candidates are extracted from low frequency wavelet sub-bands using line segment detection and the parallel density model. Finally, the geometrical properties of airfield candidates are represented by the speed-up robust features descriptor, and the support vector machine classifier is utilised to gain the final detection results. The proposed framework is evaluated on self-made dataset. Compared with the existing relevant state-of-the-art approaches, the proposed method reduces the processing time by 60% while guaranteeing the detection rate. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Optical remote sensing

来源：评论

学校读者我要写书评

暂无评论

Implementation of Automatic Face Detection System Based on ARM

Implementation of Automatic Face Detection System Based on A...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Keng Li He Chen Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology 5 South Zhongguancun Street Haidian District Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The embedded automatic face detection system is to locate the face region in the real scene. In order to reach a real-time performance, We adopt a cascaded structure of the convolution neural network model to solve face detection problem. In hardware implementation, the ARM Cortex-A9 processor is used to achieve the algorithm. And the Neon unit in ARM is used to achieve the parallel operation of the basic data of the algorithm, so the detection algorithm is accelerated to achieve the real-time operation of the automatic face detection system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Radar HRRP recognition based on CNN

Radar HRRP recognition based on CNN

引用

IET International Radar Conference 2018, IRC 2018

作者： Song, Jia Wang, Yanhua Chen, Wei Li, Yang Wang, Junfu Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China

In this study, ground target recognition based on one-dimensional convolutional neural network (CNN) is studied by exploiting the targets' high-resolution range profiles (HRRPs). Contrary to conventional methods which need feature extraction artificially, CNN can automatically discover features for classification. The authors propose a multi-channel CNN architecture that can be applied on diverse forms of HRRP such as amplitude, complex, spectrum etc. Experimental results demonstrate the superiorities of the proposed method over conventional methods based on handcrafted features and single-channel CNN in terms of recognition accuracy. Visualisation of the 'deep features' shows higher separability than handcrafted features, thus providing an insight into its effectiveness in exploiting the intrinsic structures. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Radar target recognition

来源：评论

学校读者我要写书评

暂无评论

FPGA-based accelerator for convolution operations

FPGA-based accelerator for convolution operations

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Yunfei Cao Xin Wei Tingting Qiao He Chen Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology 5 South Zhongguancun Street Haidian District Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Convolutional neural networks have been widely used in many deep learning applications. Convolutional neural networks have a large number of convolution operations, which poses a huge challenge to real-time performance. In recent years, FPGA implementations of convolutional accelerators have received much attention due to their high performance and energy efficiency. In this paper, we implement an accelerator for convolution operations through the systolic array architecture on Xilinx ZedBoard device. The experimental results show that ours designed accelerators achieving performance density of up to 0.032 Gop/s/DSP.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficient and Lightweight Target Recognition for High Resolution Spaceborne SAR Images

Efficient and Lightweight Target Recognition for High Resolu...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Yu Pan Linbo Tang Donglin Jing Wei Tang Shichao Zhou Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Fast and reliable target recognition of the synthetic aperture radar (SAR) images has been widely used in the fields of the marine monitoring, military reconnaissance and strike all over the world. However, due to the difficulty of the intra-class difference and inter-class similarity of the multiclass targets in the high resolution SAR images, the existing methods are difficult to recognize the targets accurately when facing the spaceborne platforms with the high resource constraints. Therefore, in order to solve the above problems, we propose a novel recognition method based on the convolutional neural network (CNN). Firstly, we propose a lightweight CNN framework which regards densely connected convolutional network (DenseNet) as the baseline. Secondly, we advocate a strong discriminative loss function which efficiently improves the recognition accuracy of the targets in the spaceborne SAR images. Experiments are conducted on the TerraSAR dataset and MSTAR dataset to evaluate the proposed method. The results show that our method performs better than the baseline on the both benchmark datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hyperspectral inversion for soil moisture and temperature based on Gaussian process regression

Hyperspectral inversion for soil moisture and temperature ba...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Zhen Li Chenwei Deng Baojun Zhao Yibing Tian Yun Huang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The soil moisture and temperature significantly influence the natural environment. Hyperspectral remote sensing can serve as a pivotal technique to monitor soil surface. However, modeling soil parameters encounter the following problems: hyperspectral data is high-dimensional and non-linear, and hyperspectral datasets are of limited size. In this paper, we derive a framework for inversion of soil moisture and temperature. First, wavelet transform is adopted that is able to extract the main structure of spectrum curve and reduce the dimensionality of the hyperspectral data. Then, Gaussian process regression (GPR), which is suitable for small sample data, is applied to predict the soil moisture and temperature. The experimental results show that our model outperforms other methods in estimating soil character.

关键词： soil character hyperspectral inversion wavelet transform Gaussian process regression

来源：评论

学校读者我要写书评

暂无评论

Moving target detection based on Circular Video SAR

Moving target detection based on Circular Video SAR

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Hongshuo Wang Baojun Zhao Xingsha Yang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Video Synthetic Aperture Radar (Video-SAR) achieves radar video observation by continuously monitoring a certain area to form continuous image data of the target, and it plays an important role in civil and military fields. The SAR image of the moving target is defocused and deviates from its true position, but in its real position, a shadow area similar to the target size is generated. In this paper, the shadow area is used to detect the moving target. Firstly, the image sequence is de-noised by wavelet analysis. Then the maximum threshold segmentation of Tsallis gray entropy is performed. The SIFT and FAST algorithms are used to detect and match the corners of each frame. At the same time, the RANSAC algorithm is used to optimize the pairing results to complete the image registration. Finally, the moving target is extracted by the three-frame difference method, and the result is marked to the corresponding position of the original image. Based on the Video SAR segment published by Sandia Labs in the United States, the detection of the largest moving vehicle in the video is realized, and the effectiveness and anti-interference of the proposed algorithm is verified.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cascaded Kalman filter for target tracking in automotive radar

Cascaded Kalman filter for target tracking in automotive rad...

引用

IET International Radar Conference 2018, IRC 2018

作者： Li, Yang Liang, Can Lu, Man Hu, Xueyao Wang, Yanhua Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China

In automotive anti-collision radar system, the accuracy of velocity is one of the key indicators to measure radar performance. For frequency modulation continuous wave radar with chirp sequence, which is commonly used in automotive radar, there are two problems that are velocity ambiguity and measurement error. In order to address these problems, a cascaded Kalman filter algorithm is proposed in this article, which is able to overcome velocity ambiguity and improve the accuracy of measurements. In addition, the problem of velocity ambiguity can be solved just in the data processing and it avoids transmitting staggered or multiple pulse repetition frequency signal. The simulation results show that this algorithm can effectively improve the tracking performance. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

A SAR target recognition method with frequency and spatial domain enhancement

A SAR target recognition method with frequency and spatial d...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Zhiru Wang Liang Chen Baogui Qi Guanqun Wang Hao Shi Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Synthetic aperture radar (SAR) image target recognition is a hot issue in remote sensing image application. High accuracy SAR target recognition is truly important in both military and civilian fields. Recently, convolutional neural networks (CNNs) have played an important role in the field of SAR image target recognition, however, most of the existing networks incurs some additional problems such as ignoring the influence of speckle noise on the target recognition process, so the recognition accuracy is low. To cope with these problems, this paper proposes a novel SAR image target recognition method based on CNN with frequency and spatial domain enhancement. First, the image is transformed by Gabor feature descriptor in different frequency directions to generate a plurality of feature maps. Then, the image is spatially enhanced using a Laplace transform. The feature maps which obtained by the frequency and spatial domain enhancement together with the original image are used as the network input. Finally, the improved deep residual network (ResNet) is used to complete the target recognition task. Experimental results demonstrate that the proposed method achieves a state-of-the-art accuracy on the MSTAR dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel Method for Abrupt Motion Change Radar Target Detection Based on Generalized Radon-Fourier Transform

A Novel Method for Abrupt Motion Change Radar Target Detecti...

引用

Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Siyuan Liu Zegang Ding Xu Zhou Pengjie You Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Long-time integration is an effective method to improve the signal-to-noise ratio (SNR) and detection performance of highly maneuvering targets. The existing methods for long-time integration mainly focus on detecting targets with high-order motion under fixed model, losing sight of the possibility that targets may have an abrupt motion change at an unknown instant. Therefore, this paper proposes a novel long-time integration method for highly maneuvering target with abrupt change model (ACM) based on generalized Radon-Fourier transform (GRFT), which could coherently integrate the target echoes before and after ACM and obtain the optimal coherent integration gain. The simulation and experiment results show that the proposed method can detect the ACM target under the condition of extremely low SNR and improve the detection performance compared with the fixed model GRFT.

关键词： abrupt motion change target detection highly maneuvering target detection long-time coherent integration generalized Radon-Fourier transform (GRFT)

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53页 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：