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

3,570 篇 会议
37 篇 期刊文献
8 册 图书

馆藏范围

3,615 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,582 篇 工学
- 1,048 篇 电气工程
- 1,000 篇 计算机科学与技术...
- 917 篇 测绘科学与技术
- 711 篇 信息与通信工程
- 525 篇 软件工程
- 224 篇 光学工程
- 193 篇 仪器科学与技术
- 157 篇 电子科学与技术（可...
- 155 篇 控制科学与工程
- 152 篇 航空宇航科学与技...
- 90 篇 生物工程
- 84 篇 机械工程
- 64 篇 化学工程与技术
- 63 篇 生物医学工程（可授...
- 51 篇 建筑学
- 49 篇 环境科学与工程（可...
- 47 篇 土木工程
1,446 篇 理学
- 1,031 篇 物理学
- 245 篇 数学
- 101 篇 生物学
- 93 篇 系统科学
- 86 篇 化学
- 84 篇 统计学（可授理学、...
- 43 篇 大气科学
- 33 篇 地质学
- 31 篇 地球物理学
687 篇 医学
- 685 篇 临床医学
174 篇 管理学
- 97 篇 图书情报与档案管...
- 81 篇 管理科学与工程(可...
40 篇 农学
- 31 篇 作物学
15 篇 军事学
12 篇 经济学
11 篇 法学
5 篇 文学
3 篇 教育学
2 篇 艺术学

主题

1,088 篇 remote sensing
208 篇 image processing
176 篇 feature extracti...
169 篇 image segmentati...
168 篇 synthetic apertu...
154 篇 satellites
140 篇 signal processin...
118 篇 image resolution
112 篇 image reconstruc...
112 篇 hyperspectral im...
109 篇 image classifica...
105 篇 image fusion
101 篇 deep learning
97 篇 image analysis
91 篇 spatial resoluti...
91 篇 sensors
87 篇 signal processin...
87 篇 radar imaging
86 篇 image coding
71 篇 classification

机构

27 篇 wuhan univ sch r...
20 篇 school of remote...
20 篇 beijing key labo...
19 篇 natl aerosp univ...
17 篇 institute of rem...
17 篇 beijing normal u...
15 篇 univ maryland ba...
14 篇 beijing institut...
13 篇 beijing institut...
12 篇 beijing key labo...
12 篇 beijing institut...
11 篇 univ chinese aca...
11 篇 school of inform...
11 篇 beijing key lab ...
11 篇 chinese acad sci...
11 篇 university of ch...
11 篇 univ maryland de...
10 篇 univ maryland ba...
9 篇 beijing inst spa...
9 篇 school of artifi...

作者

36 篇 bruzzone lorenzo
32 篇 chang chein-i
29 篇 zhang libao
24 篇 chehdi kacem
17 篇 vozel benoit
16 篇 bovolo francesca
15 篇 lukin vladimir v...
14 篇 chen zhenzhong
14 篇 chanussot jocely...
14 篇 chang chein- i
13 篇 farah imed riadh
12 篇 chen shih-yu
12 篇 chen liang
11 篇 middelmann wolfg...
11 篇 zhang haopeng
11 篇 benediktsson jon...
10 篇 yuan yuan
9 篇 abramov sergey k...
9 篇 li yao
9 篇 datcu mihai

语言

3,522 篇 英文
52 篇 其他
31 篇 土耳其文
9 篇 中文
2 篇 俄文

检索条件"任意字段=Conference on Image and Signal Processing for Remote Sensing IX"

共 3615 条记录，以下是621-630 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：

Multispectral image Compression Algorithm Based on Sliced Convolutional LSTM 10th

Multispectral Image Compression Algorithm Based on Sliced Co...

引用

10th International conference on Communications, signal processing, and Systems, CSPS 2021

作者： Wang, Kang Zhang, Ning Hu, Kedi Cao, Tongbo College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing210016 China Xian710065 China

ISBN: (纸本)9789811903854

The multispectral imaging which are used for remote sensing imaging has a large amount of data, so this paper proposed a deep learning method which is based on sliced convolutional LSTM for multispectral image compression. Compared with other algorithms, the proposed algorithm further compresses the multispectral images by considering the similarity between the spectra and removing the inter-spectral redundancy. The proposed algorithm is based on end to end framework which is consist of encoder, decoder, entropy coding and quantizer. In experiments, the PSNR of proposed model is compared with that of JPEG2000 to evaluate the performance of our algorithm at several different bit rates. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Optical Authenticity in Pushbroom System for Spectral Information Protection

Optical Authenticity in Pushbroom System for Spectral Inform...

引用

International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Pablo Gomez Roman Jacome Emmanuel Martinez Hans Garcia Henry Arguello Department of Electrical Electronics and Telecommunications Engineering Universidad Industrial de Santander Bucaramanga Colombia Department of Systems and Informatics Engineering Universidad Industrial de Santander Bucaramanga Colombia

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In remote sensing and environmental monitoring, the authenticity of the collected hyperspectral image (HSI) is critical since unauthorized changes could cause inaccurate evaluation. Traditional approaches ensure HSI integrity after the acquisition, leaving the data vulnerable to unauthorized access or modification before applying a protective strategy. In response, this work presents a pushbroom HSI system that integrates an authentication key on the acquisition process, ensuring the key imperceptibility without affecting performance in spectral classification tasks. In addition, this work develops an algorithm designed to simulate attacks through class modifications in the HSI. Additionally, a detection algorithm is proposed to identify modifications by comparing the signed HSI with the altered version, effectively recognizing the embedded key. The proposed method was tested using simulated data and acquired data in the optical laboratory. Results demonstrate that the system maintains classification accuracy, further enhancing imperceptibility. Additionally, modifications are detectable by the key with 99% accuracy.

关键词： Integrated optics Accuracy Authentication signal processing algorithms Optical imaging Classification algorithms Optical sensors Optical signal processing Speech processing Hyperspectral imaging

来源：评论

学校读者我要写书评

暂无评论

Multi-purpose Domain Adaptive Network for Unsupervised SAR Colorization

Multi-purpose Domain Adaptive Network for Unsupervised SAR C...

引用

European signal processing conference (EUSIPCO)

作者： Nour Aburaed Mina Al-Saad Marouane Tliba Aladine Chetouani Mohammed Q. Alkhatib M. Sami Zitouni Saeed Almansoori Hussain Al Ahmad University of Dubai Dubai UAE Universitè d'Orlèans Orléans Orlèans France Mohammed Bin Rashid Space Centre Dubai UAE

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Synthetic Aperture Radar (SAR) offers a robust form of remote sensing capable of capturing imagery under any weather or lighting conditions. This unique feature makes SAR images invaluable for monitoring environmental changes, including flood events. By analyzing SAR images taken before and after floods, researchers can identify the extents of flood-impacted areas. While combining SAR with Multispectral images (MSI) can significantly improve detection capabilities, achieving perfect co-registration between these images is often challenging. SAR colorization offers an alternative solution by using MSI as a color guide to circumvent the need for precise alignment. However, a significant limitation is the lack of corresponding MSI for the majority of publicly accessible SAR datasets, hindering the application of color-guided techniques. This study aims to address this limitation by utilizing Unsupervised Domain Adaptation (UDA) embedded with ResUNet. The core strategy involves learning from a source dataset, which includes SAR images and their corresponding MSI, and applying this knowledge to a target dataset composed solely of SAR images, thereby enabling effective SAR image colorization without direct MSI guidance. The success of this approach is evaluated based on the accuracy of flood mapping produced by the colorized SAR images. Hence, our approach achieves two purposes; unsupervised colorization and accurate flood mapping. Our framework is available through the following Github repository: https://***/NourO93/UDA_colorize.

关键词： Measurement Accuracy image color analysis signal processing Radar polarimetry Floods Synthetic aperture radar remote sensing Monitoring Software development management

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid De-Noising Method for remote sensing images

An Efficient Hybrid De-Noising Method for Remote Sensing Ima...

引用

International conference on Futuristic Communication and Network Technologies, CFCNT 2020

作者： Avudaiammal, R. Devipriya, S. Swarnalatha, A. Vijayarajan, R. Department of ECE St. Joseph’s College of Engineering OMR Chennai600119 India Division of Healthcare Advancement Innovation and Research VIT University Chennai600127 India

ISBN: (纸本)9789811646249

In recent years, analysis of remote sensing imagery has become significant due to its good representation of data in region of interest (ROI) in the world. However, the noise-corrupted satellite image data may not be capable to recognize and analyze it accurately. It necessitates the usage of suitable image de-noising that aids in improving the clarity, sharpness of image for further processing like feature extraction and enhanced analysis of the image data. In this paper, an efficient hybrid bilateral-guided (HBG) filter has been proposed that can filter noise faithfully from the satellite digital image. The attractive feature of the HBG filter is its focus on preserving edges of the original image while removing noises, thereby supporting edge detection and other image processing in a better way. Weiner filtering, median filtering, bilateral filtering, guided filtering and HBG are implemented using MATLAB R2016a on Intel core i3 system. These filtering techniques are carried out on Gaussian noise, salt-and-pepper noise and speckle noise-corrupted satellite images. The performance measures used are mean square error (MSE) and peak signal-to-noise ratio (PSNR). PSNR of HBG is 83%, 76% and 81% more than that of conventional bilateral filter, and MSE of HBG is 49%, 50% and 49% lesser than that of conventional guided filter for 50% salt-and-pepper noise, speckle noise and Gaussian noise-corrupted image, respectively. It is also proved that PSNR of proposed HBG is 74, 71 and 69% more than that of existing hybrid median Wiener filter (HMW) and MSE of HBG is 85%, 95% and 84% lesser than that of hybrid median Wiener filter (HMW) for 50% Gaussian noise, salt-and-pepper noise and speckle noise-corrupted image, respectively. Thus, the simulation outcomes show that the HBG filtering is suitable for removal of all types of noise from satellite images © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Salt and pepper noise

来源：评论

学校读者我要写书评

暂无评论

Proceedings - 2022 International conference on Information processing and Network Provisioning, ICIPNP 2022

Proceedings - 2022 International Conference on Information P...

引用

2022 International conference on Information processing and Network Provisioning, ICIPNP 2022

ISBN: (纸本)9781665464055

The proceedings contain 35 papers. The topics discussed include: research on preventive maintenance of industrial Internet based on reinforcement learning;micro-doppler effect of ship based on pendulum oscillation model;leveraging graph attention network for SDN routing performance prediction;discussion on 6G network architecture based on evolution;airship-launched multi-channel receiver design based on lora technology for typhoon information;intelligent deployment of multi-air base stations for capacity enhancement of emergency communications;DFCNI: researching on data-centric framework of cloud network integration for telecom operators;analysis of spectrum refarming methods for 5G network deployment;research on microwave imaging of airborne antenna;research on interconnection architecture for 5G inter-networks roaming;a study of remote sensing image ground segmentation on deep learning;and range imaging of integrated radar communication signal based on OFDM.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Jitter error detection and compensation method based on H-infinity filter fusion for remote sensing satellite image

Jitter error detection and compensation method based on H-in...

引用

signal, Information and Data processing (ICSIDP), IEEE International conference on

作者： Yingqi Tian Haojie Yu Ying Zhu School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Satellite jitter is a common phenomenon in high-resolution satellite applications, leading to image blurring, geometric distortion, difficulties in image stitching, and reduced spatial resolution. Therefore, accurately detecting satellite jitter and compensating for it in images is crucial. In this paper, we propose a novel framework for multispectral satellite jitter detection and compensation, which integrates the results of two different detection methods to enhance detection accuracy and effectively compensate for the images. First, dense matching is performed between the bands of the multispectral imagery to obtain the relative registration error between two bands; Then, dense control point matching is conducted between the single-band image and the corresponding Ortho-images. Next, a method based on the H-infinity filtering model is proposed to fuse the results of the two detection methods and compensate for the original image. Comparative experimental analysis shows that the compensation results after fusion exhibit significant improvements compared to those obtained using a single detection method.

关键词： Satellites Accuracy Filtering Fuses Frequency-domain analysis H infinity control Jitter Stability analysis Time-domain analysis Spatial resolution

来源：评论

学校读者我要写书评

暂无评论

A Water Body Extraction Network Based on Fusing SAR images and DEM Data

A Water Body Extraction Network Based on Fusing SAR Images a...

引用

signal, Information and Data processing (ICSIDP), IEEE International conference on

作者： Jianyu Wang Ye Tian Lei Chen Ning Wang Ningning Zhang Siao Liu Satellite Communications Branch China Telecom Co. Ltd. Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Synthetic Aperture Radar (SAR) plays a crucial role in flood monitoring and early warning systems through water body extraction techniques. However, unlike optical remote sensing images, SAR images are affected by unique imaging characteristics, including shadows, noise, and complex environments, which complicate interpretation. Most existing deep learning methods rely solely on single SAR images for model training, without incorporating additional information, leading to lower accuracy in water body interpretation, especially in challenging scenarios such as mountainous areas and densely vegetated regions. To address these challenges, we propose a water body extraction algorithm that fuses SAR images with Digital Elevation Model (DEM) data to improve the accuracy and robustness in complex environments. Four different fusion strategies are explored at both the image level and feature level, incorporating DEM and slope data into an existing encoder-decoder architecture. These enhancements effectively address the aforementioned issues. Experimental results demonstrate that the fusion approach significantly improves water body extraction precision and reduces false alarm rates compared to non-fusion methods. Through a comparative analysis of the different fusion strategies, the best approach was identified as image-level fusion using DEM data, achieving a mean Intersection over Union (mIoU) of 0.95 on the GF-Floodnet dataset.

关键词： Training Accuracy Radar imaging Feature extraction Radar polarimetry Robustness Data mining Optical sensors Synthetic aperture radar remote sensing

来源：评论

学校读者我要写书评

暂无评论

RGConvNET:A Hybrid Hyperspectral image Classification Model for Extracting Deep Features with Improved Accuracy

RGConvNET:A Hybrid Hyperspectral Image Classification Model ...

引用

Advances in signal processing, Power, Communication, and Computing (ASPCC), IEEE International conference on

作者： Vikash Ranjan Pradyut Kumar Biswal Department of Electronics and Telecommunication IIIT Bhubaneswar Bhubaneswar India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

Hyperspectral imaging (HSI) has an important role in applications like urban planning, agriculture, surveillance, and remote sensing, where it helps identify various regions and materials. Although convolutional neural networks (CNNs) have significant attainment in feature extraction and classification, they face limitations in handling the dimensionality of HSI data and cannot efficiently extract local features under geometric transformations. In order to resolve this, we suggest a hybrid HSI classification model combining Recursive Gated Convolution (RG-Convolution) and U-Net. Three RG-Convolution blocks are used to capture spatial features, while U-Net handles spectral information. A dense network with global average pooling then maps the features to different classes, reducing dimensionality. The model, tested on benchmark datasets like Pavia University and Indian Pines, achieves superior performance compared to existing methods, with an overall accuracy of 98.56% and 99.84% for Indian Pines and Pavia University dataset, respectively. This outperforms current state-of-the-art algorithms.

关键词： Accuracy Convolution Surveillance Urban planning signal processing algorithms Logic gates Feature extraction Spatial resolution Hyperspectral imaging image classification

来源：评论

学校读者我要写书评

暂无评论

Swin Transformer based Siamese Network for Thermal and Optical image Registration

Swin Transformer based Siamese Network for Thermal and Optic...

引用

IEEE signal processing and Communications Applications (SIU)

作者： Mohamed Elsaeidy İsmail Can Yağmur Hasan Fehmi Ateş Bahadir Kürşat Güntürk Department of Computer Engineering Istanbul Medipol University Istanbul Turkey Department of Computer Science Ozyegin University Istanbul Turkey

The process of multi-modal image registration is fundamental in remote sensing and visual navigation applications. However, existing image registration methods that are designed for single modality images do not provide satisfactory results when applied to multi-modal image registration. In this research, our objective is to achieve highly accurate alignment of both infrared and optical (visible range) images. To accomplish this goal, we explore the effectiveness of the Swin Transformer encoder and cosine loss in enhancing the keypoint-based image registration process. Simulation results show the improvement achieved in multi-modal registration by using a transformer based Siamese network.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Lossy compression of three-channel remote sensing images with controllable quality 27

Lossy compression of three-channel remote sensing images wit...

引用

conference on image and signal processing for remote sensing XXVII

作者： Vasilyeva, Irina Li, Fangfang Abramov, Sergey Lukin, Vladimir V. Vozel, Benoit Chehdi, Kacem Natl Aerosp Univ UA-61070 Kharkov Ukraine Univ Rennes 1 IETR UMR CNRS 6164 F-22305 Lannion France

ISBN: (数字)9781510645691

ISBN: (纸本)9781510645691;9781510645684

In this paper, we consider a problem of lossy compression of three-channel or color images with application to remote sensing. The main task of such a compression is to provide a trade-off between compression ratio and quality of compressed data that should be appropriate for solving the basic tasks as classification of sensed terrains, object detection and so on. Then, alongside with a desire to increase compression ratio, one needs to control introduced distortions (image quality) to ensure that compressed data are appropriate for further use. We propose a way to lossy compression that is based on providing quality of compressed images not worse than desired according to quality metrics. The outcome of our approach is that classification accuracy either does not get worse than for uncompressed data (and sometimes even improves) or gets worse only slightly. Earlier, we have shown that it is possible to control quality for component-wise compression of multichannel images. Here, it is demonstrated that it is possible to control quality for 3D compression. Compared to component-wise compression, 3D approach leads to two important benefits: 1) compression ratio can be almost twice larger;2) probability of correct classification can be slightly better. These benefits are confirmed for real-life three-component data acquired by Sentinel sensor using maximum likelihood-based classifier.

关键词： image lossy compression quality metrics three-channel data probability of correct classification

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362页 << < 59 60 61 62 63 64 65 66 67 68 > >>

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：