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

4,745 篇 会议
55 册 图书
12 篇 期刊文献

馆藏范围

4,812 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,154 篇 工学
- 2,814 篇 计算机科学与技术...
- 2,228 篇 软件工程
- 1,265 篇 信息与通信工程
- 761 篇 控制科学与工程
- 691 篇 生物工程
- 666 篇 光学工程
- 530 篇 电气工程
- 454 篇 生物医学工程（可授...
- 419 篇 电子科学与技术（可...
- 300 篇 网络空间安全
- 182 篇 安全科学与工程
- 164 篇 机械工程
- 160 篇 仪器科学与技术
- 159 篇 交通运输工程
- 153 篇 动力工程及工程热...
- 153 篇 化学工程与技术
- 143 篇 石油与天然气工程
1,643 篇 理学
- 709 篇 生物学
- 636 篇 物理学
- 605 篇 数学
- 242 篇 化学
- 180 篇 统计学（可授理学、...
828 篇 管理学
- 464 篇 图书情报与档案管...
- 443 篇 管理科学与工程(可...
- 119 篇 工商管理
434 篇 医学
- 363 篇 临床医学
- 246 篇 基础医学(可授医学...
- 214 篇 药学(可授医学、理...
- 106 篇 公共卫生与预防医...
125 篇 法学
- 109 篇 社会学
95 篇 农学
45 篇 经济学
44 篇 文学
33 篇 教育学
12 篇 军事学

主题

321 篇 image processing
312 篇 deep learning
230 篇 image segmentati...
191 篇 signal processin...
172 篇 image classifica...
167 篇 image enhancemen...
162 篇 computer vision
140 篇 image recognitio...
138 篇 convolutional ne...
136 篇 feature extracti...
125 篇 training
115 篇 machine learning
96 篇 computer applica...
83 篇 neural networks
83 篇 computational mo...
79 篇 visualization
78 篇 object detection
71 篇 natural language...
69 篇 semantics
68 篇 artificial intel...

机构

24 篇 chitkara univers...
17 篇 maharishi school...
15 篇 lovely professio...
15 篇 tianjin universi...
13 篇 university of ch...
12 篇 the islamic univ...
12 篇 beijing institut...
11 篇 school of comput...
11 篇 centre of interd...
10 篇 peng cheng labor...
10 篇 graphic era hill...
9 篇 national univers...
9 篇 sun yat-sen univ...
9 篇 school of comput...
9 篇 vivekananda glob...
9 篇 college of compu...
8 篇 harbin engineeri...
8 篇 school of comput...
8 篇 maharishi school...
8 篇 gla university d...

作者

13 篇 chauhan rahul
11 篇 yang yang
10 篇 anand vatsala
8 篇 kukreja vinay
8 篇 gupta rupesh
7 篇 luo xiaonan
7 篇 zhao yang
6 篇 bin wang
6 篇 pei jihong
6 篇 kumar ankit
6 篇 choudhury tanupr...
6 篇 zhu ce
6 篇 ce zhu
6 篇 kumar gaurav
6 篇 bing li
6 篇 li wei
5 篇 gill kanwarparta...
5 篇 zhiguo cao
5 篇 nagaraj p.
5 篇 singh kamred udh...

语言

4,761 篇 英文
50 篇 其他
17 篇 中文
1 篇 土耳其文

检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4812 条记录，以下是211-220 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：

Robust Real-world image Enhancement Based on Multi-Exposure LDR images 23

Robust Real-world Image Enhancement Based on Multi-Exposure ...

引用

23rd ieee/CVF Winter conference on applications of computer Vision (WACV)

作者： Ren, Haoyu Fan, Yi Huang, Stephen Oppo Mobile Telecommun Corp 3570 Carmel Mt Rd San Diego CA 92154 USA

ISBN: (纸本)9781665493468

Robust real-world image enhancement from multi-exposure low dynamic range (LDR) images is a challenging task due to the unexpected inconsistency among the input images, such as the large motion or various exposures. In this paper, we propose a novel end-to-end image enhancement network to solve this problem. After extracting contextual information from the LDR images, we design a novel matching volume to align them by considering the motion and exposure differences among the input images. A stacked hourglass with dilated convolution is further utilized to aggregate the matched feature maps to the final enhanced image. In addition, we design a weakly-supervised pairwise loss function to evaluate the color consistency in the enhanced image, which further boosts the performance. We show the effectiveness of our methods on high dynamic ranging imaging (HDR) and End-to-End image signal processing (E2E-ISP) tasks. Experimental results demonstrate that our model achieves state-of-the-art enhancement performance.

关键词： image color analysis Convolution Volume measurement Imaging Dynamic range Feature extraction Distance measurement

来源：评论

学校读者我要写书评

暂无评论

PREFAB-GEN : AD HOC image GENERATION FOR PRE-MANUFACTURING OF TIRES USING image-TO-image TRANSLATION 30

PREFAB-GEN : AD HOC IMAGE GENERATION FOR PRE-MANUFACTURING O...

引用

30th ieee international conference on image processing (ICIP)

作者： Deau, Guillaume Bourdon, Pascal Carre, Philippe Merillou, Stephane Derville, Alexandre Mourougaya, Francois Univ Limoges Univ Poitiers CNRS XLIM Poitiers France Manufacture Francaise Pneumat Michelin Clermont Ferrand France

ISBN: (纸本)9781728198354

In the pneumatic industry, quality control is an essential step in assessing tire compliance. Artificial neural networks are increasingly used to accomplish this task. Their training requires a large number of images of the controlled products. However, at the launch production of a new tire, the lack of images causes a performance loss for the network. To solve this problem, we propose to translate perfect tires computer-based images into ad hoc manufacturing context-realistic ones as pre-manufacturing step to improve robustness and ensure production quality. The challenging work is to extract features in real images and apply them to computer-based images while maintaining the original geometry. In the paper, we propose Prefab-GEN, a novel architecture based on Cycle-GAN. In the generator part, an Inception U-Net architecture is developed to enforce geometrical structure conversion and extract more detailed features. The qualitative and quantitative evaluation on tire dataset shows improvements compared with state-of-art.

关键词： image-to-image translation Unpaired data Manufacturing CycleGAN

来源：评论

学校读者我要写书评

暂无评论

Focal Network for image Restoration

Focal Network for Image Restoration

引用

ieee/CVF international conference on computer Vision (ICCV)

作者： Cui, Yuning Ren, Wenqi Cao, Xiaochun Knoll, Alois Tech Univ Munich Munich Germany Sun Yat Sen Univ Shenzhen Campus Shenzhen Peoples R China

ISBN: (纸本)9798350307184

image restoration aims to reconstruct a sharp image from its degraded counterpart, which plays an important role in many fields. Recently, Transformer models have achieved promising performance on various image restoration tasks. However, their quadratic complexity remains an intractable issue for practical applications. The aim of this study is to develop an efficient and effective framework for image restoration. Inspired by the fact that different regions in a corrupted image always undergo degradations in various degrees, we propose to focus more on the important areas for reconstruction. To this end, we introduce a dual-domain selection mechanism to emphasize crucial information for restoration, such as edge signals and hard regions. In addition, we split high-resolution features to insert multiscale receptive fields into the network, which improves both efficiency and performance. Finally, the proposed network, dubbed FocalNet, is built by incorporating these designs into a U-shaped backbone. Extensive experiments demonstrate that our model achieves state-of-the-art performance on ten datasets for three tasks, including single-image defocus deblurring, image dehazing, and image desnowing. Our code is available at https://***/c-yn/FocalNet.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on Medical image Segmentation and Encryption Using GAN

Research on Medical Image Segmentation and Encryption Using ...

引用

2023 international conference on Data Science and Network Security, ICDSNS 2023

作者： Ayyavoo, Mahalakshmi Guruviah, Velmathi School of Electrical Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350301595

Deep learning has revolutionized image processing and reached state-of-the-art performance in a variety of medical image segmentation applications. Among them, Generative Adversarial Networks (GANs) have carved out a number of fresh strategies for taking on well-known and challenging problems in medical image processing. The fact that it can provide data without explicitly modelling the probability density function has also caught the attention of the computer vision field. In this essay, we go over the study of the aforementioned methods and how they are used in medical image processing. In addition, we make an effort to evaluate the advantages of using these models based on architectural considerations and various problem scenarios. © 2023 ieee.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Translation processing Model of Complex Long Sentences Based on Feature Extraction Algorithm

Translation Processing Model of Complex Long Sentences Based...

引用

image processing and computer applications (icipca), ieee international conference on

作者： Jia Liu Wuhan Donghu University Wuhan Hubei China

With the development of information technology, patents or long sentences of science and technology with huge vocabulary and complex structure have widely appeared in people's daily work. This kind of long sentence often contains several clauses and non-predicate verb phrases, and these clauses and phrases often restrict and depend on each other, thus forming a complex language phenomenon in which there are phrases in clauses and clauses in phrases. This kind of long sentence plays a great role in the logic and rigor of English itself, but it brings considerable difficulties to machine translation. In order to solve this problem, this paper proposes a multilingual and general algorithm for complex long sentence translation based on multi-strategy analysis. The algorithm uses a combination of case-based pattern matching and rule analysis to comprehensively utilize a variety of relevant language features in the source language sentences, including grammatical semantic features, sentence length, punctuation marks Functional words and contextual conditions are used to simplify the segmentation of complex long sentences and compound the translation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SEMPART: Self-supervised Multi-resolution Partitioning of image Semantics

SEMPART: Self-supervised Multi-resolution Partitioning of Im...

引用

ieee/CVF international conference on computer Vision (ICCV)

作者： Ravindran, Sriram Basu, Debraj Adobe San Jose CA 95110 USA

ISBN: (纸本)9798350307184

Accurately determining salient regions of an image is challenging when labeled data is scarce. DINO-based self-supervised approaches have recently leveraged meaningful image semantics captured by patch-wise features for locating foreground objects. Recent methods have also incorporated intuitive priors and demonstrated value in unsupervised methods for object partitioning. In this paper, we propose SEMPART, which jointly infers coarse and fine bi-partitions over an image's DINO-based semantic graph. Furthermore, SEMPART preserves fine boundary details using graph-driven regularization and successfully distills the coarse mask semantics into the fine mask. Our salient object detection and single object localization findings suggest that SEMPART produces high-quality masks rapidly without additional post-processing and benefits from co-optimizing the coarse and fine branches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

applications of Superpixels on Phase Contrast Microscopy 5

Applications of Superpixels on Phase Contrast Microscopy

引用

5th international conference on Transdisciplinary AI, TransAI 2023

作者： On, Vincent Zahedi, Atena Phandthong, Rattapol California State University Bakersfield Department of Computer and Electrical Engineering and Computer Science BakersfieldCA United States Stem Cell Research Center University of California Irvine IrvineCA United States University of California Riverside Department of Molecular Cell and Systems Biology RiversideCA United States

ISBN: (纸本)9798350358018

Cellular microscopy is enhanced by computational paradigms such as image processing, computer vision, and machine learning. image segmentation is vital for quantifying cell images, enabling tracking and subsequent applications. Superpixel algorithms offer a promising solution to challenges in phase contrast image segmentation, as they group pixels with similar characteristics into meaningful regions. By preserving essential structural information and reducing complexity, superpixels improve accuracy in cell-related measurements and facilitate the study of dynamic cellular processes. This paper presents a comparison of popular superpixel algorithms applied to cellular microscopy, highlighting their contributions to image analysis and interpretation in cell biology research. © 2023 ieee.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

SELF-REINFORCING FOR FEW-SHOT MEDICAL image SEGMENTATION 30

SELF-REINFORCING FOR FEW-SHOT MEDICAL IMAGE SEGMENTATION

引用

30th ieee international conference on image processing (ICIP)

作者： Huang, Yao Liu, Jianming Chen, Hua Jiangxi Normal Univ Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781728198354

Few-shot learning serves as a viable solution for addressing data scarcity, thus exhibiting significant potential in the domain of medical image segmentation. In this work, we propose a simple and efficient framework for few-shot medical image segmentation, termed SRPNet, which leverages self-reinforcement between foreground and background. Notably, without the need for prior knowledge, the model autonomously adapts the segmentation effect of both foreground and background, thereby enhancing the segmentation of previously unseen classes. Experimental evaluations conducted on CT and MRI datasets demonstrate the superior performance of the proposed method compared to other state-of-the-art techniques. Code is available at https://***/q362096112/SRPNet.

关键词： Few-shot Semantic Segmentation Self-reinforcing Medical image computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Construction of CNN model based on hard-assigned coding of image features 3

Construction of CNN model based on hard-assigned coding of i...

引用

3rd ieee international conference on Power, Electronics and computer applications, ICPECA 2023

作者： Zhang, Bei Tian, Huazhe Huang, Zihao Wan, Xinghua Shu, Zhong Jingmen Daily Jingmen Mobile Media Co.Ltd Jingmen China Jingchu University of Technology School of Electronic Information Engineering Jingmen China

ISBN: (纸本)9781665472784

This paper proposes a CNN model based on hard-assigned coding processing of image features. By clearly describing the relationship between the input image sample features participating in the learning dictionary training and the atomic description features in the learning dictionary in the HC hard-assigned image feature encoding transformation, two sets of parameters are designed to calculate the input image sample features and the atomic description features in the learning dictionary. The minimum distance between them, and the HC hard-assigned image feature coding transformation is improved;the HC hard-assigned coding transformation algorithm is introduced into the last convolutional layer and pooling layer in the CNN model, and a complete CNN deep neural network is designed. Improve the model. The advantages of the model constructed in this paper are verified by experimental comparison with a variety of image feature encoding transformation algorithms. © 2023 ieee.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Variational Degeneration to Structural Refinement: A Unified Framework for Superimposed image Decomposition

Variational Degeneration to Structural Refinement: A Unified...

引用

ieee/CVF international conference on computer Vision (ICCV)

作者： Li, Wenyu Xu, Yan Yang, Yang Ji, Haoran Lang, Yue Tianjin Univ Tianjin Peoples R China Hebei Univ Technol Tianjin Peoples R China

ISBN: (纸本)9798350307184

Decomposing a single mixed image into individual image layers is the common crux of a classical category of tasks in image restoration. Several unified frameworks have been proposed that can handle different types of degradation in superimposed image decomposition. However, there are always undesired structural distortions in the separated images when dealing with complicated degradation patterns. In this paper, we propose a unified framework for superimposed image decomposition that can cope with intricate degradation patterns adaptively. Considering the different mixing patterns between the layers, we introduce a degeneration representation in the latent space to mine the intrinsic relationship between the superimposed image and the degeneration pattern. Moreover, by extracting structure-guided knowledge from the superimposed image, we further propose structural guidance refinement to avoid confusing content caused by structure distortion. Extensive experiments have demonstrated that our method remarkably outperforms other popular image separation frameworks. The method also achieves competitive results on related applications including image deraining, image reflection removal, and image shadow removal, which validates the generalization of the framework.

关键词：

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482页 << < 18 19 20 21 22 23 24 25 26 27 > >>

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：