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201-210 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：

image Pre-processing for Differential Diagnosis of Multiple Sclerosis using Brain MRI 2

Image Pre-processing for Differential Diagnosis of Multiple ...

引用

2nd IEEE international conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Memon, Khuhed Yahya, Norashikin Yusoff, Mohd Zuki Hashim, Hilwati Ali, Syed Saad Azhar Siddiqui, Shahabuddin Universiti Teknologi PETRONAS Dept. of Electrical & Electronic Engineering Perak Seri Iskandar Malaysia Universiti Teknologi PETRONAS HiCoE-CISIR Dept. of Electrical & Electronic Engineering Perak Seri Iskandar Malaysia Universiti Teknologi MARA Faculty of Medicine Department of Radiology Selangor Sungai Buloh Malaysia Center for Smart Mobility & Logistics King Fahd University of Petroleum & Minerals Aerospace Engineering Dept. Dhahran Saudi Arabia Pakistan Institute of Medical Sciences Advanced International Hospital Department of Radiology Islamabad Pakistan

ISBN: (纸本)9798350347982

Multiple sclerosis (MS) is a type of auto-immune disease affecting the human brain. One of the challenges in clinical diagnosis of MS lies in its close similarity to another type of brain auto-immune disease known as neuromyelitis optica (MNO). Hence, various researchers are looking into the development of computer-aided differential diagnosis (CADD) of MS vs. MNO. Generally, the development of the CADD, involves image pre-processing, feature extraction, statistical analysis and training and testing of the classification model. The focus of this paper is on the 2 critical pre-processing steps prior to classification of MS vs. MNO, namely skull stripping and lesion segmentation. In particular, both skull stripping and brain lesion segmentation are tested with a popular semantic segmentation technique, DeepLabV3. For comparison, a recently published technique, SynthStrip from FreeSurfer [1], developed by Harvard University is also tested for brain extraction / skull removal. Similarly for segmentation of brain lesions, Lesion Segmentation Tool in SPM Toolbox is tested and compared. The results from this study provides insight on what are the appropriate pre-processing techniques for the development of an reliable automatic differential diagnosis tool for multiple sclerosis conditions. © 2023 IEEE.

关键词： Computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

image Super-resolution Reconstruction Based on Multi-layer Parallel Residual Network 2

Image Super-resolution Reconstruction Based on Multi-layer P...

引用

2nd international conference on Computers, Information processing and advanced Education, CIPAE 2021

作者： Wang, Huifeng Xu, Yan Wei, Yiming Lanzhou Jiaotong University School of Electronic and Information Engineering Gansu China

ISBN: (纸本)9781665426657

The existing methods can improve the overall visual effect of the image, but the reconstructed image is still lack of high-frequency information, leading to texture blur. To solve these problems, this paper proposes an image super-resolution reconstruction algorithm based on multi-layer parallel convolution and residual network. Taking the multilayer parallel structure as the whole framework, firstly, different convolution combinations are used to enrich the feature information of the parallel structure, and the jump connection is added to further enrich the feature and fuse the output to extract more high-frequency information. Secondly, an adaptive residual network is introduced to supplement information and optimize network performance. Finally, perceptual loss is used to improve the overall quality of the restored image. Experimental results show that the proposed algorithm performs well for the reconstructed image, and the PSNR and structural similarity are significantly improved in the objective evaluation. © 2021 IEEE.

关键词： Adaptive systems Convolution Superresolution Reconstruction algorithms Feature extraction Visual effects Nonhomogeneous media

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Machine Intelligence and signal processing, MISP 2021

3rd International Conference on Machine Intelligence and Sig...

引用

3rd international conference on Machine Intelligence and signal processing, MISP 2021

ISBN: (纸本)9789811908392

The proceedings contain 67 papers. The special focus in this conference is on Machine Intelligence and signal processing. The topics include: Internet of Things: A Survey on Fused Machine Learning-Based Intrusion Detection Approaches;image Fusion-Based Watermarking in IWT-SVD Domain;on Twin Bounded Support Vector Machine with Pinball Loss;traffic Rule Violation Detection System: Deep Learning Approach;template-Based Thinning Method for Handwritten Gujarati Character’s Strokes and its Classification for Writer-Dependent Gujarati Font Synthesis;a Model on Intrusion Detection Using Firefly Algorithm and Classical Machine Learning;deep Learning Framework Based on Audio–Visual Features for Video Summarization;a Comparative Study of Deep Learning Models for Word-Sense Disambiguation;MultiYOLO: Learning New YOLO Categories Without Full Retraining;Analysis of Fifteen Approaches to Automated COVID-19 Detection Using Radiography images;vehicle Routing Problem Using Reinforcement Learning: Recent Advancements;disease Detection of Plant Leaves with the Aid of Region Growing and Neural Network: A Comparative Analysis;a Web Application for Early Prediction of Diabetes Using Artificial Neural Network: A Comparative Study;machine Learning Equipped Web-Based Disease Prediction and Recommender System;comparing the Predictive Accuracy of Machine Learning algorithms for Neonatal Mortality Risk Classification;Extraction of Waterbody Using Object-Based image Analysis and XGBoost;Deep Learning-Based image Retrieval in the JPEG Compressed Domain;fake News Detection Using Genetic Algorithm-Based Feature Selection and Ensemble Learning;Application of SPSS for Forecasting of Renewable Energy as Future Energy in India;robust Multi-task Least Squares Twin Support Vector Machines for Classification;human Emotion Classification Based on Speech Enhancement Using Neural Networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Medical image Watermarking Scheme in Transform Domain based on Asymmetric crypto-system and Arnold Chaotic Map 44

Medical Image Watermarking Scheme in Transform Domain based ...

引用

44th international conference on Telecommunications and signal processing (TSP)

作者： Nadhir, Nouioua Ali, Seddiki Abdelkrim, Ghaz Univ Djillali Liabes Sidi Bel Abbes Telecommun & Digital Signal Proc Lab Sidi Bel Abbes Algeria Univ Djillali Liabes Sidi Bel Abbes Commun Networks Architectures & Multimedia Lab Sidi Bel Abbes Algeria

ISBN: (纸本)9781665429337

Sharing a secret via the internet needs huge protection challenges to keep it in clean hands, and far away from several ways of maleficent manipulations, e.g., hacking and spying. Nowadays, experts proposed many encryption algorithms that work in spatial domain as well as frequency domain, to provide certain amount of privacy for this public network navigators. The proposed algorithm is about embedding an encrypted Electronic Patient Record (EPR) in Discrete Cosine Transform (DCT) resultant of a medical image that is decomposed into third level with Discrete Wavelet Transform (DWT), where the EPR is encrypted using Elgamal encryption, and Arnold map is also exerted in order to increase the randomness and unpredictability levels and to make the algorithm more complex. A variety of tests has been performed to prove the proposed scheme robustness.

关键词： Arnold Chaotic Map Discrete Cosine Transform Discrete Wavelet Transform Elgamal Crypto-System Medical images Digital Watermarking

来源：评论

学校读者我要写书评

暂无评论

DECOMPOSING TEXTURES USING EXPONENTIAL ANALYSIS

DECOMPOSING TEXTURES USING EXPONENTIAL ANALYSIS

引用

IEEE international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Hou, Yuan Cuyt, Annie Lee, Wen-shin Bhowmik, Deepayan Univ Antwerp Dept Comp Sci B-2020 Antwerp Belgium Univ Stirling Div Comp Sci & Math Stirling FK9 4LA Scotland Shenzhen Univ Coll Math & Stat Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9781728176055

Decomposition is integral to most image processing algorithms and often required in texture analysis. We present a new approach using a recent 2-dimensional exponential analysis technique. Exponential analysis offers the advantage of sparsity in the model and continuity in the parameters. This results in a much more compact representation of textures when compared to traditional Fourier or wavelet transform techniques. Our experiments include synthetic as well as real texture images from standard benchmark datasets. The results outperform FFT in representing texture patterns with significantly fewer terms while retaining RMSE values after reconstruction. The underlying periodic complex exponential model works best for texture patterns that are homogeneous. We demonstrate the usefulness of the method in two common vision processing application examples, namely texture classification and defect detection.

关键词： Exponential analysis multivariate image decomposition texture analysis

来源：评论

学校读者我要写书评

暂无评论

Compressive Sensing Magnetic Resonance image Reconstruction and Denoising using Convolutional Neural Network 1

Compressive Sensing Magnetic Resonance Image Reconstruction ...

引用

1st international conference on Artificial Intelligence, Computational Electronics and Communication System, AICECS 2021

作者： Singh, Ram Kaur, Lakhwinder Department of Computer Science and Engineering Punjabi University Patiala India

Restoration of high-quality brain Magnetic Resonance image (MRI) from the sparse under-sampled complex k-space signal is a widely studied ill-posed inverse transform problem. A deep learning-based data-adaptive and data-driven convolutional technique has been proposed for high-quality MRI recovery from its under-sampled complex domain k-space signal. The uniform subsampling process is very slow in phase-encoding to generate high-resolution images. The longer scan times degrade the perceptual image quality. Various factors contribute to image degradation during data acquisition such as the inception of body motion artifacts, the thermal energy effects of the body, and random noise artifacts due to voltage fluctuations. Keeping in view the patient's critical condition and comfort, longer scan times are not preferred in practice. To reduce the image acquisition time, noise levels, and motion artifacts in the MR images, Compressive Sensing (CS) provides an accelerated way to reconstructs the high-quality MR image from very limited signal measurements acquired much below the Nyquist rate. However, such data acquisition strategies require advanced computer algorithms for the reconstruction of high-quality MRI from the undersampled MRI data. An improved CNN-based MRI reconstructed algorithm has been presented in this paper which shows better performance to reconstruct high-quality MRI than similar other MR image reconstruction algorithms. The performance of the proposed algorithm is measured by image quality checking tools such as normalized-MSE, PSNR, and SSIM. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： image reconstruction

来源：评论

学校读者我要写书评

暂无评论

SEMASUPERPIXEL: A MULTI-CHANNEL PROBABILITY-DRIVEN SUPERPIXEL SEGMENTATION METHOD

SEMASUPERPIXEL: A MULTI-CHANNEL PROBABILITY-DRIVEN SUPERPIXE...

引用

IEEE international conference on image processing (ICIP)

作者： Wang, Xuehui Zhao, Qingyun Fan, Lei Zhao, Yuzhi Wang, Tiantian Yan, Qiong Chen, Long Sun Yat Sen Univ Guangzhou Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China Northwestern Univ Evanston IL 60208 USA City Univ Hong Kong Hong Kong Peoples R China SenseTime Res Beijing Peoples R China

ISBN: (纸本)9781665441155

Superpixel, an efficient image segmentation approach, aggregates a group of similar pixels into the same cluster. Existing superpixel algorithms still mainly focus on the color information while ignoring the semantic distribution knowledge. In this paper, we propose a semantic information-driven method that adopts multi-channel semantic probabilities for superpixel segmentation. By conducting statistical analysis on the semantic output and then formulating the distance measure, the prior knowledge of the semantic with a dynamic confidence value could be utilized by our method during the global update effectively. Extensive experimental evaluations show that our method achieves a leading segmentation quality and convergence speed, compared to other five state-of-the-art algorithms, as measured by boundary recall, undersegmentation error, and explained variation.

关键词： Superpixel segmentation image segmentation image processing

来源：评论

学校读者我要写书评

暂无评论

Can Existing image Quality Metrics Assess Enhanced images? 4

Can Existing Image Quality Metrics Assess Enhanced Images?

引用

4th international conference on Information Communication and signal processing, ICICSP 2021

作者： Huang, Gehang Liu, Xinwei HDU-ITMO Joint Institute Hangzhou Dianzi University Hangzhou China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China

ISBN: (纸本)9781665407571

Most of image quality metrics are designed for degraded images, and their performance are highly correlated with the human visual system. The rapid development of image enhancement techniques raises a new issue: how to evaluate the performance of image enhancement methods? It is obvious that many benefits can be obtained if existing image quality metrics can be applied to the performance evaluation of image enhancement algorithms. However, quite a few studies have investigated such an issue. In this paper, we conduct psychophysical experiments to investigate the performance of existing image quality metrics on enhanced images. Two databases that specifically designed for enhanced images are selected in the experiments for the collection of subjective evaluation results. The objective evaluation results are obtained from six selected image quality metrics. By calculating the correlation between subjective and objective results we can answer the question: the performance of existing selected image quality metrics is low on enhanced images. © 2021 IEEE.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

ADVMIX: DATA AUGMENTATION FOR ACCURATE SCENE TEXT SPOTTING

ADVMIX: DATA AUGMENTATION FOR ACCURATE SCENE TEXT SPOTTING

引用

IEEE international conference on image processing (ICIP)

作者： Huang, Yizhang Fang, Kun Huang, Xiaolin Yang, Jie Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai Peoples R China

ISBN: (纸本)9781665441155

Accurate scene text spotting models ask for effective data augmentation algorithms. This paper presents a novel data augmentation algorithm called AdvMix that integrates techniques of adversarial attack and mixup. First, it utilizes the PGD method to synthesize adversarial samples. Second, it is the first work to implement feature-wise mixup between original data and the associated adversarial sample to enhance data augmentation. AdvMix has been evaluated over ICDAR2013 and ICDAR2015 datasets, showing its superior performance in improving accuracy of scene text spotting models.

关键词： Scene Text Spotting Data Augmentation AdvMix Adversarial Attack

来源：评论

学校读者我要写书评

暂无评论

Lightweight image Dehazing Neural Network Model Based on Estimating Medium Transmission Map by Intensity 19th

Lightweight Image Dehazing Neural Network Model Based on Est...

引用

19th Pacific Rim international conference on Artificial Intelligence (PRICAI)

作者： Jin, Tian-Hu Tao, Yan-Yun Guo, Jia-Ren Huang, Zi-Hao Zheng, Jian-Yin Soochow Univ Sch Rail Transportat Suzhou 215000 Peoples R China Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Minist Educ Shanghai 200240 Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9783031208676;9783031208683

Single image dehazing is a challenging ill-posed problem. The key to achieve haze removal is to estimate an accurate medium transmission map. By redefining the atmospheric scattering model, we obtain a new transmittance map scattering model, haze image and haze-free image, derive the medium transmission as a function of the scene intensity only, also deduce a priori condition that the intensity of hazy image is higher than that of haze-free image, and propose a lightweight image dehazing neural network (Intensity neural network, I-Net) based on estimating medium transmission map by intensity. I-Net uses a convolutional neural network (CNN) as the backbone, and takes the intensity of hazy image as the input, and outputs the intensity of haze-free image, the medium transmission map and the original haze-free image, also joints the priori condition derived previously to obtain a more accurate medium transmittance map. In this paper, the dehazing algorithm obtains the intensity of haze-free image through I-Net, derives the transmittance map using the functional relationship between transmittance and scene intensity, and finally recovers the original haze-free image through the transmittance map scattering model. The experimental results show that our dehazing results are clearer and more natural. The subjective and objective evaluations show that our image dehazing algorithm can achieve better dehazing results than traditional algorithms, and outperforms current advanced algorithms in terms of Peak signal to Noise Rate (PSNR) and Structure Similarity Index Measurement (SSIM).

关键词： Single image dehazing Atmospheric scattering model Medium transmission map Deep CNN

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 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：