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

3,569 篇 会议
37 篇 期刊文献
8 册 图书

馆藏范围

3,614 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,581 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
- 710 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
51 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 3614 条记录，以下是281-290 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：

Infrared-to-Optical image Translation for Keypoint-Based image Registration 30

Infrared-to-Optical Image Translation for Keypoint-Based Ima...

引用

30th IEEE signal processing and Communications Applications conference (SIU)

作者： Elsaeidy, Mohamed Erkol, Muhammed Emin Gunturk, Bahadir Kiirsat Ates, Hasan Fehmi Istanbul Medipol Univ Dept Comp Engn Istanbul Turkey Istanbul Medipol Univ Dept Elect & Elect Engn Istanbul Turkey

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450928

Multi-modal image registration is a critical step in many remote sensing and visual navigation applications. While image registration techniques developed for single modality images do not perform well for multi-modal registration, techniques developed for multi-modal image registration are not suitable for real-time applications. In this study, we aim to achieve real-time registration of infrared and optical (visible range) images. Specifically, we investigate the use of image-to-image translation deep network to convert infrared images to optical images, which is then applied for keypoint-based image registration.

关键词： Multi-modal image registration GAN image translation network

来源：评论

学校读者我要写书评

暂无评论

DCUNet: Deformable Convolutional UNet for Multi-frame Infrared Small Target Super-resolution 2

DCUNet: Deformable Convolutional UNet for Multi-frame Infrar...

引用

2nd IEEE International conference on signal, Information and Data processing, ICSIDP 2024

作者： Huang, Yuanxin Zhi, Xiyang Chen, Wenbin Liang, Xiaoyang Wang, Zhipeng Zhang, Wei Harbin Institute of Technology Research Center for Space Optical Engineering Harbin China China Academy of Space Technology Institute of Remote Sensing Satellite Beijing China

ISBN: (纸本)9798331515669

The objective of infrared multi-frame super-resolution for small targets is to enhance the target's resolution by leveraging complementary information from multiple frames. However, the presence of motion variations and scale changes in infrared small targets introduces discontinuities in information between frames, posing challenges for super-resolution. To address the above challenges, we propose a multi-frame infrared small target super-resolution network based on deformable UNet. Specifically, the network takes multi-frame sequential infrared images as input and divides the input into reference frames and current frames. It utilizes deformable convolutions to align the frames to enhance the target features of the current frame. Additionally, the encoding structure of the UNet network is employed to extract multiscale features from the sequential images. By leveraging skip connections and a decoding structure, the network achieves the enhancement of target detail information and the fusion of multiscale features, ultimately outputting the super-resolved image. We conducted experiments on the IRDST and NUDT-MIRSDT datasets, and the results validate the practicality of our designed network. © 2024 IEEE.

关键词： Optical resolving power

来源：评论

学校读者我要写书评

暂无评论

Fast on-board ship detection in panchromatic images based on micro-nano satellite 28

Fast on-board ship detection in panchromatic images based on...

引用

conference on image and signal processing for remote sensing XXVIII

作者： Qi, Jing Guo, Chen Zhang, Haopeng DFH Satellite Co Ltd Beijing 100094 Peoples R China Beihang Univ Sch Astronaut Dept Aerosp Informat Engn Beijing 102206 Peoples R China Beijing Key Lab Digital Media Beijing 102206 Peoples R China Minist Educ Key Lab Spacecraft Design Optimizat & Dynam Simul Beijing 102206 Peoples R China

ISBN: (纸本)9781510655386;9781510655379

With the continuous improvement of the number and capability of micro-nano satellites, on-board intelligent data processing becomes a necessary configuration. The constellation with hundreds micro-nano satellites has the ability to high-frequency detection of ship targets and realizes continuous awareness of the global ocean, which is of great significance in maritime rescue, waterway management and combating illegal fishing. In this paper, a fast on-board ship detection method for panchromatic image is proposed. Firstly, GPU (graphics processing unit) of commercial devices is used to form high performance and low power computing capability on the micro-nano satellite. Then, according to the characteristics of ship targets, a convolutional neural network based on lightweight model is designed to quickly obtain accurate number and location information of ship targets. The algorithm deployed on micro-nano satellite can transform massive remote sensing data into target slices, greatly reduce the pressure of satellite-ground data transmission and improve the application efficiency of remote sensing data. We test our method on a dataset of more than 90 panchromatic images. The results show that the detection rate of this algorithm is better than 0.95, and the average processing speed for a image block of 1024 x 1024 pixel is less than 0.2 seconds, which has a wide application prospect.

关键词： Ship detection on-board processing micro-nano satellite

来源：评论

学校读者我要写书评

暂无评论

A novel Illumination Normalization Based on 2D Recursive Convex Optimization

A novel Illumination Normalization Based on 2D Recursive Con...

引用

IET International Radar conference 2023, IRC 2023

作者： Yan, Yaqiong Shi, Ji Cai, Maoxin Zhao, Jiafei Beijing Institute of Remote Sensing Device Beijing China

ISBN: (纸本)9781839539954

Illumination normalization is fundamental and critical to image preprocessing in terms of improving signal to Clutter Ratio (SCR), contrast, etc. Whereas previous studies mostly focused on image sequence, we propose in this paper a new approach that deals with a single image with uneven illumination. The proposed approach firstly performs image division based on the Auto Regressive Moving Average (ARMA) model and then implements illumination normalization separately for different types of backgrounds applying a two-dimensional recursion convex optimization method. Unlike techniques based on consecutive frames, this method is capable of treating images with drastic changes in background yet requiring only mild assumption on the image, making it adaptable to various situations. Simulation results show its effectiveness in improving the contrast and SCR of an image. © The Institution of Engineering & Technology 2023.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

STAW-Net: Spatio-Temporal Attentional Windmill Network for Tropical Cyclone Intensity Prediction 2

STAW-Net: Spatio-Temporal Attentional Windmill Network for T...

引用

2nd IEEE International conference on signal, Information and Data processing, ICSIDP 2024

作者： Wang, Cong Chen, Zhao Wang, Qian Minhas, Fayyaz Donghua University School of Computer Science and Technology Shanghai201620 China University of Warwick Tissue Image Analytics Centre Department of Computer Science United Kingdom

ISBN: (纸本)9798331515669

Tropical cyclone (TC) intensity prediction using remote sensing images plays an important role in weather forecast and disaster prevention. Though having achieved great success in image analysis, deep learning methods lack feature extractors specifically designed for TC structures, resulting in limited representation capabilities for TC structure. Moreover, most of these methods overlook that TC is a temporal system with strong time dependencies. To this end, we propose a spatiotemporal attentional windmill network (STAW-Net) for TC intensity prediction. Specifically, we extract temporal-spatial-spectral features from multi-temporal TC multispectral images (MSIs). Notably, we design a novel Windmill Convolution (WMConv) to simulate the dynamic characteristics of TC occurrence and to extract structural features related to the TC eye region. Finally, we combine these temporal-spatial-spectral features with structural features to predict the maximum sustained wind (MSW) speed. Experimental results show that STAW-Net outperforms many baselines and state-of-the-art methods on various cyclone datasets. The errors of 24-hours MSW prediction by STAW-Net can be as low as 6.37m/s and 5.64m/s for the TCIR and the HURSAT-B1 datasets, respectively. © 2024 IEEE.

关键词： Tropical cyclone

来源：评论

学校读者我要写书评

暂无评论

A MULTI-STAGE DUPLEX FUSION CONVNET FOR AERIAL SCENE CLASSIFICATION 29

A MULTI-STAGE DUPLEX FUSION CONVNET FOR AERIAL SCENE CLASSIF...

引用

IEEE International conference on image processing (ICIP)

作者： Yi, Jingjun Zhou, Beichen Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

Existing deep learning based methods effectively prompt the performance of aerial scene classification. However, due to the large amount of parameters and computational cost, it is rather difficult to apply these methods to multiple real-time remote sensing applications such as on-board data preception on drones and satellites. In this paper, we address this task by developing a light-weight ConvNet named multi-stage duplex fusion network (MSDF-Net). The key idea is to use parameters as little as possible while obtaining as strong as possible scene representation capability. To this end, a residual-dense duplex fusion strategy is developed to enhance the feature propagation while re-using parameters as much as possible, and is realized by our duplex fusion block (DFblock). Specifically, our MSDF-Net consists of multi-stage structures with DFblock. Moreover, duplex semantic aggregation (DSA) module is developed to mine the remote sensing scene information from extracted convolutional features, which also contains two parallel branches for semantic description. Extensive experiments are conducted on three widely-used aerial scene classification benchmarks, and reflect that our MSDF-Net can achieve a competitive performance against the recent state-of-art while reducing up to 80% parameter numbers. Particularly, an accuracy of 92.96% is achieved on AID with only 0.49M parameters.

关键词： Light-weight ConvNet Aerial Scene Classification Duplex Fusion Duplex Semantic Aggregation

来源：评论

学校读者我要写书评

暂无评论

Research on Target Detection Algorithms for Site Safety Equipment

Research on Target Detection Algorithms for Site Safety Equi...

引用

2024 International conference on remote sensing, Mapping, and image processing, RSMIP 2024

作者： Xing, Jiacheng State Grid Beijing Information & Telecommunication Company Beijing China

ISBN: (纸本)9781510680012

Safety helmets are the most common and practical personal protection tool on construction sites and can effectively prevent and mitigate head injuries caused by accidents. Detecting safety helmets and various safety equipment is a major task in the safety management of construction site personnel. It is also an important element in the intelligent monitoring technology of construction sites. With the development of artificial intelligence, it has now become an important part of intelligent construction site construction. The safety equipment target detection algorithm is investigated to comprehensively analyze the research status of artificial intelligence technology in safety equipment detection. In this paper, after introducing the attention mechanism into the yolov5s algorithm and adding the density residual module RDB and the cavity density residual module DRDB proposed in this paper, the accuracy of identifying helmet wearers is improved by 1.4% for aerial scenes and about 1.2% for seat belt wearers, and the accuracy of identifying helmet wearers is also improved slightly for ground scenes. © 2024 SPIE.

关键词： signal detection

来源：评论

学校读者我要写书评

暂无评论

A Robust Methodology for Reducing Noise and Artifacts in Digital images using image Denoising with Filtering Strategy 8

A Robust Methodology for Reducing Noise and Artifacts in Dig...

引用

8th International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Gayathri, J. Prerna, D. Yuvaraj, S. Sivani, V. Saveetha School of Law Chennai600 077 India

ISBN: (纸本)9798350376425

image denoising is a critical task in various fields, including medical imaging, remote sensing, and photography, where noise and artifacts can significantly degrade image quality. This study proposes a robust methodology for reducing noise and artifacts in digital images using a hybrid image denoising strategy that integrates Median, Gaussian, and Bilateral filtering techniques. The proposed model was evaluated using the Berkeley Segmentation Dataset and Benchmark (BSDS500) and compared against nine existing models. The results demonstrate that the proposed methodology outperforms existing models across multiple metrics, achieving a Peak signal-to-Noise Ratio (PSNR) of 32.10 dB, a Structural Similarity Index (SSIM) of 0.890, a Feature Similarity Index (FSIM) of 0.948, and an Edge Preservation Index (EPI) of 0.889. The model also achieved the lowest Mean Squared Error (MSE) of 24.90 and the fastest processing time of 1.20 seconds, highlighting its effectiveness in reducing noise while preserving image details. These findings suggest that the proposed methodology is highly suitable for applications requiring precise and efficient image denoising. The study's approach offers a comprehensive solution that balances noise reduction with the preservation of critical image features, making it a valuable contribution to the field of image processing. © 2024 IEEE.

关键词： Bilateral Filter Gaussian Filter Hybrid Filtering Strategy image Denoising Median Filter Noise Reduction

来源：评论

学校读者我要写书评

暂无评论

Spatial-Frequency Information Interaction Diffusion for SAR Colorization

Spatial-Frequency Information Interaction Diffusion for SAR ...

引用

2025 IEEE International conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Zhang, Xupei Qin, Hanlin Li, Jingjing Geng, Jinni Gao, Zihan Yu, Yue School of Optoelectronic Engineering Xidian University Xi'an710071 China Xi'an Key Laboratory of Infrared Technology and System Xi'an710071 China

ISBN: (纸本)9798350368741

The inherent speckle noise and grayscale characteristics of synthetic aperture radar (SAR) images pose challenges to information perception and interpretation. To address this issue, we propose a novel conditional diffusion model with spatial-frequency information interaction for SAR colorization, namely SFI4SC. Specifically, we introduce a learnable wavelet transform module to obtain the global frequency information of the input SAR image and then take it as a guiding condition to assist the diffusion model for SAR colorization. Additionally, we improved the network structure for the diffusion model by designing and introducing a spatial and frequency information interaction module to achieve multidimensional information interaction for the network inputs, further enhancing perceptual details and geometric structures of the SAR colorization results. Experimental results in the real-world remote sensing dataset show that our approach can successfully enhance visual clarity and informational content while preserving the unique characteristics of the SAR images. The code will be made publicly available. © 2025 IEEE.

关键词： Diffusion Model image colorization Spatial-Frequency Interaction Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Point cloud restoration via 2D projection and inpainting 28

Point cloud restoration via 2D projection and inpainting

引用

conference on image and signal processing for remote sensing XXVIII

作者： Mai, Adrian Bilinski, Mark Provost, Raymond Hess, Michael NIWC Pacific 49275 Electron Dr San Diego CA 92152 USA

ISBN: (纸本)9781510655386;9781510655379

The presence of noise, displacement of points, and empty spots in a raw Light Detection and Ranging (LiDAR) point cloud are common phenomena caused by reflective surfaces or objects. Typical approaches to solve this problem are either avoid or cover the reflective areas or to manually remove the erroneous data in post processing. This can help clean the point cloud structure but will cause sparsity issues. To combat this, in this paper, we introduce a two-step process to perform point cloud restoration. Instead of removing noise, this approach can restore the points to the closest surface which they may belong to. Next, to fill out empty spots, we introduce a technique called point cloud inpainting, which involves interpolating points in 2D then mapping it back to 3D for flat surfaces. The point cloud then becomes more photorealistic and easier to use for other computer vision tasks.

关键词： Clouds 3D image processing image processing 3D acquisition Associative arrays Data processing LIDAR Machine vision Optical character recognition Scanners

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 << < 25 26 27 28 29 30 31 32 33 34 > >>

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：