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

674 篇 会议
12 册 图书
5 篇 期刊文献

馆藏范围

691 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

451 篇 工学
- 322 篇 计算机科学与技术...
- 258 篇 软件工程
- 196 篇 信息与通信工程
- 138 篇 电气工程
- 84 篇 生物工程
- 72 篇 光学工程
- 64 篇 生物医学工程（可授...
- 34 篇 电子科学与技术（可...
- 24 篇 化学工程与技术
- 22 篇 控制科学与工程
- 19 篇 材料科学与工程（可...
- 17 篇 仪器科学与技术
- 13 篇 机械工程
- 12 篇 安全科学与工程
- 9 篇 动力工程及工程热...
- 8 篇 交通运输工程
- 6 篇 网络空间安全
235 篇 理学
- 110 篇 物理学
- 87 篇 生物学
- 85 篇 数学
- 22 篇 化学
- 19 篇 统计学（可授理学、...
- 9 篇 系统科学
104 篇 医学
- 102 篇 临床医学
- 23 篇 基础医学(可授医学...
- 20 篇 药学(可授医学、理...
- 6 篇 公共卫生与预防医...
72 篇 管理学
- 43 篇 图书情报与档案管...
- 31 篇 管理科学与工程(可...
6 篇 法学
6 篇 教育学
- 6 篇 教育学
5 篇 农学
2 篇 军事学

主题

98 篇 signal processin...
58 篇 image segmentati...
58 篇 image processing
54 篇 signal processin...
43 篇 conferences
41 篇 deep learning
38 篇 image enhancemen...
33 篇 image recognitio...
29 篇 feature extracti...
28 篇 training
24 篇 image edge detec...
24 篇 convolution
24 篇 visualization
24 篇 image color anal...
24 篇 image reconstruc...
22 篇 image coding
22 篇 image classifica...
20 篇 neural networks
18 篇 robustness
17 篇 object detection

机构

6 篇 school of inform...
6 篇 college of elect...
5 篇 key laboratory o...
5 篇 university of ch...
5 篇 nanyang technol ...
5 篇 school of mathem...
4 篇 shanghai jiao to...
4 篇 laboratory of be...
4 篇 school of electr...
3 篇 shanghai jiao to...
3 篇 michigan state u...
3 篇 college of mathe...
3 篇 tsinghua shenzhe...
3 篇 shanghai jiao to...
3 篇 national laborat...
2 篇 university of sc...
2 篇 school of comput...
2 篇 school of cyber ...
2 篇 school of mathem...
2 篇 huazhong univers...

作者

6 篇 wang chao
6 篇 yang chuansheng
5 篇 yang yueting
5 篇 wen bihan
5 篇 yang jian
4 篇 jian wang
4 篇 tan anhui
4 篇 anil kumar
4 篇 bo feng
4 篇 chao xu
3 篇 ravishankar saip...
3 篇 zhou jiantao
3 篇 li min
3 篇 zhai guangtao
3 篇 nguyen trong-the
3 篇 feng bo
3 篇 parthasarathy ra...
3 篇 xiaotao huang
3 篇 wang liu
3 篇 fan zhun

语言

691 篇 英文

检索条件"任意字段=2021 International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2021"

共 691 条记录，以下是41-50 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：

Clothing image retrieval method based on ConvNeXt 3

Clothing Image retrieval method based on ConvNeXt

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Shi, Xiujin Zhang, Yiwei Donghua University Songjiang Shanghai China

ISBN: (纸本)9781510668522

This article proposes a clothing image retrieval method based on the ConvNeXt network. This research uses the ConvNeXt network, which is obtained by improving and adjusting the classic ResNet50 network based on some advanced ideas of the transformer network, as a feature extractor to conduct research on a subset (In-Shop Clothes Retrieval) of the DeepFashion dataset. In order to improve model training speed and retrieval performance, this article uses transfer learning, which utilizes the ConvNeXt network model pre-Trained on the imageNet-1k dataset. Considering the limitations of using only a global branch, a local branch is added, and the global branch and local branch are trained together during training. During retrieval, only global features are used, as local features help global features learn some knowledge of the local features, resulting in better results. Experimental results show that this method can extract more expressive clothing image features and effectively improve clothing image retrieval performance. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： image retrieval

来源：评论

学校读者我要写书评

暂无评论

A novel blind medical image watermarking scheme in NSST domain based on schur decomposition and DWT 3

A novel blind medical image watermarking scheme in NSST doma...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Gao, Han Zheng, Weimin College of Computer Science and Engineering Shandong University of Science and Technology Qingdao Shandong266590 China

ISBN: (纸本)9781510668522

Nowadays, medical images face numerous information security challenges. On the one hand, medical images should be associated with patient information while ensuring data security and privacy protection. On the other hand, with the increasing use of technologies such as deep learning in medical images, there is a growing concern about copyright protection for medical image data used for sharing and training. Digital watermarking technology presents a potential solution to address these issues. This paper proposes a medical image watermarking scheme that utilizes Schur decomposition in combination with non-subsampled shearlet transform (NSST), discrete wavelet transform (DWT) and region of interest (ROI) identification for minimizing modifications to the original image. Furthermore, our proposed scheme does not require the original cover image for watermark extraction, reducing the reliance on additional information. The proposed method has been tested under various type of attacks, and the results have shown that it has high robustness and imperceptibility. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： image watermarking

来源：评论

学校读者我要写书评

暂无评论

Quantum image encryption based on hyper-chaotic system and double-random phase encoding 3

Quantum image encryption based on hyper-chaotic system and d...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Wu, Lei Li, Meiju Jia, Jiyang Sun, Xiaofei School of Information Science and Engineering Zaozhuang University Shandong277160 China

ISBN: (纸本)9781510668522

In order to enhance the security of encrypted images, a new quantum image encryption algorithm is proposed. This algorithm combines Chen's hyper-chaotic system with Double-random Phase Encoding (DRPE). The pixel values of the original quantum image are diffused using DRPE, while the pixel positions are scrambled through Cyclic Translation (CT). The hyper-chaotic sequences generated by Chen's hyper-chaotic system control the scrambling and diffusion operations. Numerical simulations and theoretical analyses have shown that this algorithm is highly effective in resisting illegal attacks. The encrypted image generated by this algorithm exhibits lower pixel correlation and more evenly distributed histogram. Overall, the proposed algorithm represents a robust and secure approach for image encryption © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Research and implementation of image edge detection based on Db4 wavelet transform 3

Research and implementation of image edge detection based on...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Li, Donghui Yuan, Wei Chen, Xu Guan, Xuehui Liu, Dayu Harbin Cambridge University China

ISBN: (纸本)9781510668522

Wavelet transform is a new time-frequency domain analysis tool after Fourier transform. Wavelet analysis has very important applications in image processing, including image compression, image denoising, image fusion, image decomposition and image enhancement and so on almost all stages of image processing. By comparing several edge detection methods and combining the multi-scale characteristics of wavelet transform, the approximate coefficient and high frequency coefficient of wavelet transform decomposition are processed, and an image edge detection algorithm based on wavelet transform is proposed. In the MATLAB environment, firstly, taking an image as an example, Roberts operator, Sobel operator, Prewitt operator and Canny operator are compared to verify that Canny operator has better performance in edge location. Then the db4 wavelet is applied to this image and the other two images, the image is decomposed and reconstructed, and the Canny operator is used for edge detection. The simulation results show that the edge details extracted by this method are more abundant. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Edge detection

来源：评论

学校读者我要写书评

暂无评论

Study on feature extraction of cable surface defect image based on morphology and edge detection algorithm

Study on feature extraction of cable surface defect image ba...

引用

2021 international conference on advanced algorithms and signal image processing, aasip 2021

作者： Hu, Jing He, Hongyu Liao, Guomin Hu, Guichuan School of Intelligent Manufacturing Chongqing College of Architecture and Technology Chongqing China School of mechanical and power engineering Chongqing University of science and technology Chongqing China School of Digital Engineering Chongqing College of Architecture and Technology Chongqing China

The cable-stayed bridge has been widely used because of its excellent bearing capacity, beautiful structure and relatively low construction cost. As one of the most important mechanical components in long-span cable-stayed bridges, the safety of bridge cables is the focus of attention. the image of cable surface defect was taken as the object, and carrying out the image pretreatment. On the basis, through analysis and comparison, the image of cable crack was processed by morphological gradient operation, meanwhile the Sobel operator was selected to detect the cable surface defect image. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Surface defects

来源：评论

学校读者我要写书评

暂无评论

ECT image reconstruction based on improved multi-scale residual network 2

ECT image reconstruction based on improved multi-scale resid...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Ma, Min Wu, Huan Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9781510660571

In order to solve the soft field effect in capacitance tomography lead to the problem of low quality of image reconstruction, this paper proposes an image reconstruction algorithm based on improved multi-scale residual network(IMRN), by introducing a multi-scale convolution structure layer information, abundant feature extracting multi-scale empty convolution structure, and then build a change with different expansion rate convolution receptive field, The global feature information is obtained and the number of network parameters is effectively reduced. The channel attention mechanism is used to weight the extracted features adaptively and filter the redundant information. Finally, the shallow features and the extracted features of each structure are fused to compensate the lost feature information. Simulation results show that compared with LBP algorithm, Landweber iterative algorithm and 1DCNN algorithm, the improved algorithm effectively improves the quality of image reconstruction. © 2022 SPIE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Advancing ultrasound image segmentation with a hybrid framework: Integrating convolutional neural networks and active contours 3

Advancing ultrasound image segmentation with a hybrid framew...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Tao, Fu Jie, Zhou Capital Normal University College of Mathematics Beijing010-68907003 China

ISBN: (纸本)9781510668522

Ultrasound image segmentation is a critical task in computer vision and medical image analysis. Accurate segmentation of key objects in ultrasound images is essential for clinical diagnosis. In this paper, we propose a novel hybrid method that combines convolutional neural networks and active contours for ultrasound image segmentation. The proposed method aims to enhance the accuracy and robustness of ultrasound image segmentation. The CNN model extracts features from the ultrasound images, while the active contour model refines segmentation boundaries. We evaluate the proposed method on a publicly available dataset of thyroid ultrasound images and demonstrate its superior performance compared to stateof-The-Art methods. Our results show that the proposed method achieves an average Dice Similarity Coefficient of 0.91, which is significantly better than the 0.87 DSC achieved by the U-Net method. The proposed method can provide more accurate and robust segmentation of key objects in ultrasound images, which can facilitate clinical diagnosis and treatment planning. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

image Recognition Model of Contour Extraction and Shape Recognition Based on Multiple Fusion algorithms 2

Image Recognition Model of Contour Extraction and Shape Reco...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Xu, Song Xu, Changjie Tong, Lihong Wan, Qiwei Ding, Haibin State Key Laboratory of Performance Monitoring and Guarantee of Rail Transportation Infrastructure Jiangxi Nanchang330013 China Institute of Geotechnical Engineering School of Civil Engineering and Architecture East China Jiaotong University Jiangxi Nanchang330013 China

ISBN: (纸本)9781510660571

As the basic part of the field of image recognition, image edge contour extraction technology is facing more and more challenges with the deepening of image recognition technology in daily life. Based on multi-operator fusion ecological expansion method, an image edge extraction algorithm was proposed in this paper. The hybrid algorithm can eliminate the influence of some unfavourable conditions such as background noise, illumination reflective noise and extract the edge contours of single or multiple objects more accurately. According to the geometric characteristics of lines and arcs, we summarized and put forward a general method for judging whether a point sequence is a straight line or an arc, and a problem is solved based on this method, which proves the superiority of this method in the classification of contour types. Combined the existing research results and practical experience, we summarized a set of sub-pixel interpolation methods with high precision, high efficiency, and high feasibility. © 2022 SPIE.

关键词： image fusion

来源：评论

学校读者我要写书评

暂无评论

Adaptive biogeography based optimizer evolution depth convolutional neural network for image classification 3

Adaptive biogeography based optimizer evolution depth convol...

引用

3rd international conference on advanced algorithms and signal image processing, aasip 2023

作者： Nan, Xiang Parthasarathy, Rajamohan Faculty of Engineering Built Environment and Information Technology SEGi University Kota Damansara Malaysia

ISBN: (纸本)9781510668522

How to extract and analyze feature information from significantly different image data, and achieve precise positioning and classification of massive images, is the core issue of image classification research. The dataset in this article contained 10 different types of images, each with approximately 5000 images, with image sizes of 100 × 100, 200 × 200, and 300 × 300. In order to deal with large-scale data, this paper used adaptive biogeographical optimizer and traditional gradient descent methods to optimize multi-layer depth Convolutional neural network (CNN), and designed single-layer adaptive biogeographical network, multi-layer adaptive biogeographical network, single-layer gradient descent network and multilayer gradient descent network for experiments. All classifiers used the softmax function for classification. The accuracy of multi-layer network image classification under the algorithm in this article was 96.6%. The accuracy and efficiency of image classification can be improved by using Biogeography optimization algorithm to optimize the depth CNN. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： image classification

来源：评论

学校读者我要写书评

暂无评论

Research and design of image super-resolution algorithm based on attention mechanism 2

Research and design of image super-resolution algorithm base...

引用

2nd international conference on advanced algorithms and signal image processing, aasip 2022

作者： Tang, Yu Wang, Zi-Yi College of Computer and Information Science Chongqing Chongqing Normal University Chongqing China

ISBN: (纸本)9781510660571

image super-resolution algorithm is a technology that changes the image from low-resolution to high-resolution. It is widely used in various fields, including but not limited to image compression technology, satellite remote sensing imaging, urban traffic monitoring, medical imaging and so on. At present, the method based on deep learning has a very good effect on the super-resolution processing of low-resolution images, but some algorithms still have some problems, such as the loss of detail texture of the reconstructed image, and the large gap between the reconstruction results and the computational resources. To solve the above problems, this paper proposes a network model based on channel attention mechanism. The network model consists of three parts: the first part is a shallow feature extraction block, which is composed of a convolution layer and an activation layer, which is mainly used to extract the low-level features of the input image;The second part is the deep extraction block based on the channel attention mechanism, and the depth separable convolution is added to the local residual block of this part to effectively reduce the huge parameters generated by training. This module mainly extracts the high-level features of the input image;The third part is the reconstruction module, which is used to fuse the original image features extracted from the previous two parts and output the reconstructed image. Finally, the experimental results show that using this method will effectively improve the peak signal-to-noise ratio and structural similarity index of the reconstructed image. © 2022 SPIE.

关键词： Convolution

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70页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：