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

309 篇 会议
174 篇 期刊文献

馆藏范围

483 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

321 篇 工学
- 153 篇 信息与通信工程
- 142 篇 计算机科学与技术...
- 122 篇 软件工程
- 55 篇 控制科学与工程
- 50 篇 仪器科学与技术
- 41 篇 光学工程
- 34 篇 电子科学与技术（可...
- 34 篇 生物工程
- 31 篇 环境科学与工程（可...
- 30 篇 测绘科学与技术
- 22 篇 电气工程
- 21 篇 航空宇航科学与技...
- 20 篇 机械工程
- 13 篇 土木工程
- 12 篇 建筑学
- 10 篇 材料科学与工程（可...
- 10 篇 网络空间安全
- 8 篇 化学工程与技术
- 6 篇 动力工程及工程热...
163 篇 理学
- 89 篇 数学
- 45 篇 物理学
- 36 篇 生物学
- 26 篇 统计学（可授理学、...
- 19 篇 化学
- 7 篇 大气科学
- 7 篇 地球物理学
- 6 篇 系统科学
35 篇 管理学
- 18 篇 图书情报与档案管...
- 16 篇 管理科学与工程(可...
25 篇 农学
- 25 篇 农业资源与环境
3 篇 医学
2 篇 经济学
2 篇 艺术学
1 篇 法学
1 篇 军事学

主题

59 篇 synthetic apertu...
25 篇 feature extracti...
22 篇 image coding
22 篇 training
19 篇 radar polarimetr...
19 篇 remote sensing
16 篇 semantics
16 篇 radar imaging
15 篇 encoding
15 篇 image reconstruc...
14 篇 image segmentati...
14 篇 visualization
13 篇 satellites
12 篇 deep neural netw...
12 篇 three-dimensiona...
12 篇 mathematical mod...
11 篇 object detection
11 篇 video coding
11 篇 decoding
10 篇 distortion

机构

139 篇 cas key laborato...
57 篇 aerospace inform...
55 篇 key laboratory o...
54 篇 school of electr...
42 篇 institute of ele...
40 篇 university of ch...
34 篇 key laboratory o...
23 篇 key laboratory o...
19 篇 department of au...
13 篇 the cas key labo...
13 篇 key laboratory o...
13 篇 key laboratory o...
12 篇 suzhou aerospace...
9 篇 microsoft resear...
9 篇 graduate univers...
8 篇 cas key laborato...
7 篇 the cas key labo...
6 篇 university of sc...
6 篇 key laboratory o...
6 篇 national key lab...

作者

45 篇 chen zhibo
35 篇 qiu xiaolan
34 篇 li houqiang
27 篇 xiaolan qiu
26 篇 dong liu
25 篇 liu dong
24 篇 ding chibiao
23 篇 zhibo chen
23 篇 houqiang li
22 篇 li li
20 篇 zhou wengang
19 篇 zhou wei
18 篇 chibiao ding
18 篇 zhang zhe
17 篇 wu yirong
17 篇 feng wu
16 篇 zhang bingchen
15 篇 li xin
14 篇 xian sun
14 篇 bin lei

语言

469 篇 英文
7 篇 其他
7 篇 中文

检索条件"机构=CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System"

共 483 条记录，以下是221-230 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：

SEMI-SUPERVISED OBJECT DETECTION IN REMOTE SENSING IMAGES USING GENERATIVE ADVERSARIAL NETWORKS

SEMI-SUPERVISED OBJECT DETECTION IN REMOTE SENSING IMAGES US...

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Guowei Chen Lei Liu Wenlong Hu Zongxu Pan Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Object detection is a challenging task in computer vision. Now many detection networks can get a good detection result when applying large training dataset. However, annotating sufficient amount of data for training is often time-consuming. To address this problem, a semi-supervised learning based method is proposed in this paper. Semi-supervised learning trains detection networks with few annotated data and massive amount of unannotated data. In the proposed method, Generative Adversarial Network is applied to extract data distribution from unannotated data. The extracted information is then applied to improve the performance of detection network. Experiment shows that the method in this paper greatly improves the detection performance compared with supervised learning using only few annotated data. The results prove that it is possible to achieve acceptable detection result when only few target object is annotated in the training dataset.

关键词： Gallium nitride Generative adversarial networks Detectors Generators Airplanes Training Semisupervised learning

来源：评论

学校读者我要写书评

暂无评论

DRBOX FAMILY: A GROUP OF OBJECT DETECTION TECHNIQUES FOR REMOTE SENSING IMAGES

DRBOX FAMILY: A GROUP OF OBJECT DETECTION TECHNIQUES FOR REM...

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Lei Liu Zongxu Pan Guowei Chen Yizhao Gao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Objects in remote sensing images are difficult to detect due to arbitrarily rotated angles and the wide variance of scales. As bounding box plays an important role in object detection, we proposes a new bounding box type named rotated bounding box (rBox). With the application of rBox, we have proposed a series of detection techniques (DrBox, DrBoxLight, DrBoxSemi, DrBoxPro) to effectively handle the situation where the orientation angles of the objects are arbitrary. This article is a brief overview of these techniques. The original DrBox detector applies VGG-net as its main network framework, with image pyramid input to address multi-scale problem. DrBoxLight is a mini version of DrBox, which applies MobileNet and knowledge distillation to be deployed on embedded devices. DrBoxSemi is a semi-supervised version of DrBox, so annotation of all training samples is no longer necessary. DrBoxPro is the most important update for DrBox with professional designing of abundant prior-rBoxes on feature pyramid networks. In our experiments, we demonstrated how rBox helps to improve the performance of object detection compared with traditional bounding boxes. Besides, we evaluated the performance of our DrBox family on a series of object detection tasks.

关键词： Object detection Remote sensing images Rotated object Deep learning

来源：评论

学校读者我要写书评

暂无评论

Inshore Ship Detection in Sar Images Based on Deep Neural Networks

Inshore Ship Detection in Sar Images Based on Deep Neural Ne...

引用

IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Lei Liu Guowei Chen Zongxu Pan Bin Lei Quanzhi An Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Inshore ship detection in SAR image faces difficulties on correctly identifying near-shore ships and onshore objects. This article proposes a multi-scale full convolutional network (MS-FCN) based sea-land segmentation method and applies a rotatable bounding box based object detection method (DR-Box) to solve the inshore ship detection problem. The sea region and land region are separated by MS-FCN then DR-Box is applied on sea region. The proposed method combines global information and local information of SAR image to achieve high accuracy. The networks are trained with Chinese Gaofen-3 satellite images. Experiments on the testing image show most inshore ships are successfully located by the proposed method.

关键词： Marine vehicles Image segmentation Synthetic aperture radar Reliability Merging Image resolution

来源：评论

学校读者我要写书评

暂无评论

AUTOMATIC WATER DETECTION METHOD IN FLOODING AREA FOR GF-3 SINGLE-POLARIZATION DATA

AUTOMATIC WATER DETECTION METHOD IN FLOODING AREA FOR GF-3 S...

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Deke Tang Feng Wang Yuming Xiang Hongjian You Wenchao Kang Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

China is a flood disaster-prone country, floods occur almost every year, especially in July and August. Rapid detection and assessment for floods affected areas are of great significance. The Chinese GF-3 SAR satellite, which uses active ground observation technology, has obvious advantages in flood disaster monitoring owing to its all-day, all-weather imaging characteristics. For the purpose of rapid water detection in flooding area, an automatic detection method of flood area based on GF-3 single-polarization SAR data is proposed. The proposed method consists of image preprocessing and water extraction. The experimental results show that the proposed method can realize rapid and accurate extraction of waters in flood disaster area.

关键词： Floods Synthetic aperture radar Data mining Imaging Satellites Manuals Urban areas

来源：评论

学校读者我要写书评

暂无评论

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Feng Wang Yuming Xiang Xinghui Yao Jiayin Liu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

The conventional shape similarity measurements of remote sensing data face problems in the situation of noise interference, partial information occlusion and missing. A method of shape similarity measurement based on principal curvature enhancement distance transformation is proposed. The distance transformation is carried out to extend the range of the shape contour, improving the robustness of the similarity measure. Besides, to ensure the accuracy of measurement results, the distance map is enhanced by the principal curvature of the shape contour, improving the response of contours with rich information. application experiments of road vectors with GPS data and optical remote sensing images show that the method is effective in practical application.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ionosphere Estimation and Correction for geosynchronous SAR based on point target deviation between Range Sub-images

Ionosphere Estimation and Correction for Geosynchronous SAR ...

引用

2016 IEEE 13th International Conference on Signal processing（ICSP2016）

作者： Huang Lijia Ding Chibiao Qiu Xiaolan Zhang Hongyi Li Liang Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of ElectronicsChinese Academy of Sciences

Ionosphere is an important factor in highresolution spaceborne synthetic aperture radar（SAR） and geosynchronous（geo） SAR. An approach based on point target deviation between range sub-images is proposed in this paper to estimate and correct the ionosphere. Due to the dispersion effect, the ionosphere causes propagation delay deviation in range subimages with different carrier frequency. This deviation can be used to estimate the total electron content（TEC） along the propagation path, and then the ionospheric effects can be corrected according to the signal model deduced out in this paper. The simulation results show that our approach is valid and robust.

关键词： Spaceborne Synthetic Aperture Radar（SAR） geosynchronous（geo） SAR Ionospheric Effects Estimation and Correction

来源：评论

学校读者我要写书评

暂无评论

An Invariant Generalized Hough Transform Based Method of Inshore Ships Detection

An Invariant Generalized Hough Transform Based Method of Ins...

引用

International Symposium on Image and Data Fusion (ISIDF)

作者： Jian Xu Kun Fu Xian Sun Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Automatic inshore ship detection from remote sensing imagery has many important applications, such as ship change detection and harbor dynamic surveillance. Stable performance of inshore ship detection is vital to the analysis of ship change and then determines the harbor surveillance effect. However, it is hard to detect inshore ships utilizing the traditional area-based method because the grayscale and texture character of inshore ships are similar to that of the shore. In this paper, a new method based on invariant generalized Hough transform is introduced to extract ship shape using the evidence-gathering procedure. In contrast with other shape extraction methods used in inshore ships detection, our method is specially tolerant to noise and occlusion, and also invariant to translation, scale and rotation transformation. Moreover, our method can be used to separate ships moored together that can benefit to ship recognition. Experiment results are demonstrated on the optical remote sensing imagery from Google Earth.

关键词： Marine vehicles Image edge detection Transforms Noise Remote sensing Indexes Shape

来源：评论

学校读者我要写书评

暂无评论

A new endmember extraction algorithm by maximum ASC fraction

A new endmember extraction algorithm by maximum ASC fraction

引用

Workshop on Hyperspectral Image and Signal processing: Evolution in Remote Sensing, WHISPERS

作者： Luyan Ji Xiurui Geng Yongchao Zhao Key Laboratory of Technology in Geo-spatial information Processing and Application System Chinese Academy of Science Beijing China

This paper presents a new simplex-based method for unsupervised endmember extraction, called maximum abundance sum-to-one constraint (ASC) fraction (MAF). The ASC fractions refer to the spectral unmixing results with the abundance sum-to-one constraint unmixing only. The algorithm assumes the existence of the pure pixels in the input data for every endmember in the scene, and exploits the fact that pixels with maximum ASC fractions are corresponding to the vertices of a simplex. In order to demonstrate the performance of the proposed MAF, the N-findr algorithm (N-FINDR) and vertex component analysis (VCA) based merely on PCA dimensional reduction are used for comparison. Experiments using both simulated and real hyperspectral data show that MAF is effective in searching optimal results, with a low computational complexity.

关键词： Abstracts Complexity theory

来源：评论

学校读者我要写书评

暂无评论

SAR TARGET CLASSIFICATION WITH CYCLEGAN TRANSFERRED SIMULATED SAMPLES

SAR TARGET CLASSIFICATION WITH CYCLEGAN TRANSFERRED SIMULATE...

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Lei Liu Zongxu Pan Xiaolan Qiu Lingxiao Peng Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Target classification is an important part in automatic target recognition (ATR) systems. Deep learning methods get state of the art performance in SAR target classification. Simulation is a useful data augmentation method when the numbers of real samples for training is not sufficient. This article discusses how to release the full potential of simulated samples which is used to improve performance of SAR target classifier. The proposed method is based on cycle adversarial network (CycleGAN), which can transfer simulated samples to be more similar with real samples in image domain. Experiments show that adding simulated samples straightforward into training dataset is not helpful to improve the performance. However, adding the transferred simulated samples for training results in about 10% increase in accuracy in the designed SAR airplane classification experiment, compared with training without data augmentation.

关键词： Training Testing Synthetic aperture radar Azimuth Gallium nitride Data models Airplanes

来源：评论

学校读者我要写书评

暂无评论

SUPER-RESOLUTION OF REMOTE SENSING IMAGES BASED ON TRANSFERRED GENERATIVE ADVERSARIAL NETWORK

SUPER-RESOLUTION OF REMOTE SENSING IMAGES BASED ON TRANSFERR...

引用

IEEE International geoscience and Remote Sensing Symposium

作者： Wen Ma Zongxu Pan Jiayi Guo Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China

Single image super-resolution (SR) has been widely studied in recent years as a crucial technique for remote sensing applications. This paper proposes a SR method for remote sensing images based on a transferred generative adversarial network (TGAN). Different from the previous GAN-based SR approaches, the novelty of our method mainly reflects from two aspects. First, the batch normalization layers are removed to reduce the memory consumption and the computational burden, as well as raising the accuracy. Second, our model is trained in a transfer-learning fashion to cope with the insufficiency of training data, which is the crux of applying deep learning methods to remote sensing applications. The model is firstly trained on an external dataset DIV2K and further fine-tuned with the remote sensing dataset. Our experimental results demonstrate that the proposed method is superior to SRCNN and SRGAN in terms of both the objective evaluation and the subjective perspective.

关键词： Remote sensing images Super-resolution Generative adversarial network Transfer learning

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49页 << < 19 20 21 22 23 24 25 26 27 28 > >>

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：