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

4,427 篇 会议
237 篇 期刊文献
54 册 图书
8 篇 学位论文
3 篇 资讯

馆藏范围

4,729 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,630 篇 工学
- 1,501 篇 计算机科学与技术...
- 893 篇 电气工程
- 771 篇 软件工程
- 465 篇 信息与通信工程
- 331 篇 控制科学与工程
- 291 篇 生物医学工程（可授...
- 224 篇 光学工程
- 210 篇 机械工程
- 164 篇 电子科学与技术（可...
- 141 篇 仪器科学与技术
- 125 篇 生物工程
- 90 篇 材料科学与工程（可...
- 68 篇 测绘科学与技术
- 58 篇 化学工程与技术
- 32 篇 土木工程
- 27 篇 建筑学
- 25 篇 力学（可授工学、理...
1,480 篇 理学
- 926 篇 物理学
- 657 篇 数学
- 431 篇 统计学（可授理学、...
- 228 篇 系统科学
- 138 篇 生物学
- 63 篇 化学
755 篇 医学
- 592 篇 临床医学
- 218 篇 特种医学
- 74 篇 基础医学(可授医学...
- 44 篇 药学(可授医学、理...
214 篇 管理学
- 119 篇 管理科学与工程(可...
- 103 篇 图书情报与档案管...
- 25 篇 工商管理
24 篇 农学
17 篇 法学
13 篇 教育学
11 篇 经济学
10 篇 艺术学
9 篇 文学
2 篇 军事学

主题

550 篇 image processing
464 篇 image segmentati...
385 篇 stochastic proce...
371 篇 statistical anal...
261 篇 feature extracti...
230 篇 bayesian methods
221 篇 image reconstruc...
188 篇 signal processin...
185 篇 image analysis
142 篇 pixel
135 篇 image restoratio...
110 篇 statistics
106 篇 image edge detec...
104 篇 pattern recognit...
104 篇 image coding
103 篇 hidden markov mo...
99 篇 noise reduction
96 篇 image denoising
95 篇 robustness
94 篇 visualization

机构

10 篇 school of electr...
8 篇 indian statistic...
7 篇 univ penn dept r...
7 篇 department of el...
7 篇 department of el...
7 篇 univ waterloo de...
7 篇 univ michigan de...
6 篇 nanyang technol ...
6 篇 smart computer v...
6 篇 computer vision ...
5 篇 georgia inst tec...
5 篇 microsoft resear...
5 篇 carnegie mellon ...
5 篇 signal and image...
5 篇 peng cheng lab p...
4 篇 google res mount...
4 篇 texas a&m univ.
4 篇 department of sy...
4 篇 ivan kozhedub kh...
4 篇 tokyo metropolit...

作者

9 篇 landman bennett ...
8 篇 vorapoj patanavi...
8 篇 dougherty er
8 篇 h. krim
7 篇 yannick berthoum...
7 篇 a.s. willsky
7 篇 sang hwa lee
6 篇 astola jaakko t.
6 篇 prince jerry l.
6 篇 umapada pal
6 篇 alexander wong
6 篇 udupa jk
6 篇 nam ik cho
6 篇 w. pieczynski
6 篇 fessler jeffrey ...
6 篇 w.c. karl
6 篇 pesquet jean-chr...
6 篇 pal umapada
6 篇 jong-il park
6 篇 pieczynski w

语言

4,600 篇 英文
87 篇 其他
31 篇 中文
13 篇 土耳其文
1 篇 西班牙文
1 篇 法文
1 篇 俄文

检索条件"任意字段=Conference on Statistical and Stochastic Methods for Image Processing"

共 4729 条记录，以下是1021-1030 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：

A Generic Approach CNN-Based Camera Identification for Manipulated images 3

A Generic Approach CNN-Based Camera Identification for Manip...

引用

IEEE 3rd International conference on Signal and image processing (ICSIP)

作者： El-Yamany, Ahmed Fouad, Hossam Raffat, Youssef Alghoniemy, Masoud Univ Alexandria Dept Elect Engn Alexandria 21544 Egypt

ISBN: (纸本)9781538663967

Camera model identification has been attracting a lot of attention lately, as a powerful forensic method. With the promising breakthroughs in the artificial intelligence applications, such systems were revisited to increase the expected accuracy or to solve the still persisting deadlocks. One of the most still-to-be-solved dilemmas is the image manipulations effect on the overall accuracy of the identification systems. A huge degradation in the performance is noticed, when images are post-processed using commonly used methods as compression, scaling and contrast enhancement. Using the state of the art Convolutional Neural Network (CNN) architecture proposed by Bayar et al to estimate the manipulation parameters, and dedicated feature extractor models to estimate the source camera. Multiplexers are used to shift the input image between the dedicated models through the output of the CNNs. Our proposed methods significantly outperform state of the art methods in the literature, especially in case of heavy compression and down sampling. The images used for testing were extracted from 10 different cameras, including different models from the same manufacturer. Different devices were used to investigate the methodology robustness. Moreover, such generic approach could revolutionary change the whole design methodology for camera model identification systems.

关键词： Camera Model Identification CNN Demosaicing Local Binary Pattern (LBP) statistical Compression Down-Sampling Enhancement

来源：评论

学校读者我要写书评

暂无评论

Sorting Pixels based Face Recognition Using Discrete Wavelet Transform and statistical Features

Sorting Pixels based Face Recognition Using Discrete Wavelet...

引用

International conference on Imaging, Signal processing and Communication (ICISPC)

作者： A. Divya K. B. Raja K.R. Venugopal University Visvesvaraya College of Engineering Bangalore University Bangalore India Bangalore University Bangalore India

Face recognition is used to identity a person effectively and most effective physiological biometric trait. In this paper, we propose sorting pixels-based face recognition using Discrete Wavelet Transform (DWT) and statistical features. The novel concept of sorting pixel values in ascending order is introduced and segmented into two parts viz., Low Pixel Values (LPV) and High Pixel Values (HPV). The DWT is applied on LPV matrix to generate low and high frequency bands such as LL, LH, HL and HH. The low frequency LL band is considered for features as the coefficient values are enhanced compared to original image pixel values and also reduction in dimensionality. The statistical measure is applied on HPV to compute mean, median, mode, maximum and standard deviation features. The features of LL band and statistical features are concatenated to obtain final features. The Artificial Neural Network (ANN) is used as classifier to recognize human beings. It is perceived that the performance of the proposed method is enhanced compared with the existing methods.

关键词： Face recognition Face Discrete wavelet transforms Feature extraction Training Sorting Databases

来源：评论

学校读者我要写书评

暂无评论

A statistical Model for image Registration Performance: Effect of Tissue Deformation

A Statistical Model for Image Registration Performance: Effe...

引用

conference on Medical Imaging - image processing

作者： Ketcha, M. D. De Silva, T. Han, R. Uneri, A. Jacobson, M. W. Vogt, S. Kleinszig, G. Siewerdsen, J. H. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Siemens Healthcare XP Div Erlangen Germany

ISBN: (数字)9781510616387

ISBN: (纸本)9781510616387

Purpose: The accuracy of image registration is a critical factor in image-guidance systems, so it is important to quantifiably understand factors that fundamentally limit performance of the registration task. In this work, we extend a recently derived model for the effect of quantum noise on registration error to a more "generalized" model in which tissue deformation is incorporated as an additional source of "noise" described by a power-law distribution, analogous to "anatomical clutter" in signal detection theory. methods: We apply a statistical framework that incorporates objective image quality factors such as spatial resolution and image noise combined with a statistical representation of anatomical clutter to predict the root-mean-squared error (RMSE) of transformation parameters in a rigid registration. Model predictions are compared to simulation studies in CT-to-CT slice registration using the cross-correlation (CC) similarity metric. Results: RMSE predictions are shown to accurately model the impact of dose and soft-tissue clutter on measured RMSE performance. Further, these predictions reveal dose levels at which the registration becomes soft-tissue clutter limited, where further increase provides no improvement in registration performance. Conclusions: Incorporating tissue deformation into a statistical registration model is an important step in understanding the limits of image registration performance and selecting pertinent registration methods for a particular registration task. The generalized noise model and RMSE analysis provide insight on how to optimize registration tasks with respect to image acquisition protocol (e.g., dose, reconstruction parameters) and registration method (e.g., level of blur).

关键词： CT/CBCT Fisher Information image-Guided Procedures image Quality image Registration Performance Limits

来源：评论

学校读者我要写书评

暂无评论

Coffee Leaf Disease Recognition Based on Deep Learning and Texture Attributes 23rd

Coffee Leaf Disease Recognition Based on Deep Learning and T...

引用

23rd KES International conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)

作者： Boa Sorte, Lucas Ximenes Ferraz, Carolina Toledo Fambrini, Francisco Goulart, Roseli dos Reis Saito, Jose Hiroki UNIFACCAMP Univ Ctr Campo LimpoPaulista SP Campo Limpo Paulista SP Brazil Univ Fed Sao Carlos Sao Carlos SP Brazil Fed Inst South Minas Gerais Agr Dept Muzambinho MG Brazil

An automatic coffee plant disease recognition system is required since coffee is an important commodity in the world economy and its productivity and quality are affected by diseases such as Cercospora and Rust. This research aims to apply computational methods to recognize main diseases in coffee leaves, with the purpose to implement an expert system to assist coffee producers in disease diagnosis during its initial stages. Since these two diseases are shapeless, it inspires a texture attribute extraction approach for pattern recognition. Two texture attributes were considered in this work: statistical attributes and local binary patterns. The texture attribute vector were computed for a collection of images of coffee leaves and used as input to a feedforward neural network. The results were compared with the recognition rate of a convolutional neural network with deep learning applied directly to the same collection of images, without extraction of texture attributes. Surprisingly, this second approach showed better results than the texture extraction method. It could be explained by the small number of diseases we aimed to recognize and a sufficient number of training samples used during the deep learning process. The best Kappa coefficient obtained was 0.970, and sensitivity was 0.980. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Thermography image processing coffee leaf disease cercospora rust Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of the Ground clutter suppression on Meteorological images

A comparative analysis of the Ground clutter suppression on ...

引用

International conference on image and Signal processing and their Applications (ISPA)

作者： Mehdia Hedir Fethi Demim Boualem Haddad Image Processing and Radiation Laboratory USTHB Algiers Algeria Laboratoire des Vehicules Autonomous Intelligents Ecole Militaire Polytechnique Bordj EI Bahri Algeria IPR Laboratory Faculty of Electronic and Informatics USTHB Algiers Algeria

ISBN: (纸本)9781728131573

Local Binary Pattern (LBP) is a gray scale-invariant local operator, it is encoded with each pixel by neighbourhood thresholding which is considered as powerful and simple in the case of real-time implementation. The latter is efficient in characterizing the texture and can be adapted to different problems. Different descriptors have been developed that are based on LBP . In our case, we chose Local Phase Quantization (LPQ), Local Ternary Patterns (LTP), Binarized statistical image Features (BSIF), Multiblock Local Binary Pattern (MB -LBP ) to characterize meteorological images and make a comparative analysis between these different methods. Since the objective is to distinguish between precipitation and non-precipitation pixels, we inject the characteristic at the input of a SV M classifier. The approaches were performed on two databases taken from Setif (Algeria) and Bordeaux (France). The experiments show that the best results are obtained by combining LBP to the variance for Setif while the addition of BSIF and LPQ gives the best results when considering the Bordeaux region.

关键词： SVM model QPE LBP LPQ BSIF LTP LBP gene LBP Long-Term Potentiation Ground clutter clutter suppression binary pattern pixel

来源：评论

学校读者我要写书评

暂无评论

image processing Based Method For Identification Of Fish Freshness Using Skin Tissue 4

Image Processing Based Method For Identification Of Fish Fre...

引用

International conference on Computational Intelligence and Communication Technology (CICT)

作者： Sengar, Namita Gupta, Varun Dutta, Malay Kishore Travieso, Carlos M. Amity Univ Dept Elect & Commun Engn Noida India Univ Las Palmas Gran Canaria Signals & Commun Dept Las Palmas Gran Canaria Spain

ISBN: (纸本)9781538608869

The quality of the fish is mainly altered by different cooling methods, exporting, handling etc. In this paper a non-destructive framework is proposed for identification of fish freshness using image processing techniques. In this paper skin tissue is selected as focal tissue for basic analysis and identification of freshness of fish from fish images. statistical features are extracted in the HSV color space which gives degradation pattern for fish freshness which is used to design the framework for identification of fish freshness. The experiment result indicates monotonic degradation pattern. Experiments were carried on fish images and results are encouraging. The maximum classification accuracy of contributed methodology is 96.66%.

关键词： Fish Freshness Skin Tissue image processing

来源：评论

学校读者我要写书评

暂无评论

Fully Point-wise Convolutional Neural Network for Modeling statistical Regularities in Natural images 18

Fully Point-wise Convolutional Neural Network for Modeling S...

引用

26th ACM Multimedia conference (MM)

作者： Zhang, Jing Cao, Yang Wang, Yang Wen, Chenglin Chen, Chang Wen Hangzhou Dianzi Univ Hangzhou Peoples R China Univ Sci & Technol China Hefei Peoples R China Univ Buffalo State Univ New York Buffalo NY USA

ISBN: (纸本)9781450356657

Modeling statistical regularity plays an essential role in ill-posed image processing problems. Recently, deep learning based methods have been presented to implicitly learn statistical representation of pixel distributions in natural images and leverage it as a constraint to facilitate subsequent tasks, such as color constancy and image dehazing. However, the existing CNN architecture is prone to variability and diversity of pixel intensity within and between local regions, which may result in inaccurate statistical representation. To address this problem, this paper presents a novel fully point-wise CNN architecture for modeling statistical regularities in natural images. Specifically, we propose to randomly shuffle the pixels in the origin images and leverage the shuffled image as input to make CNN more concerned with the statistical properties. Moreover, since the pixels in the shuffled image are independent identically distributed, we can replace all the large convolution kernels in CNN with point-wise (1 * 1) convolution kernels while maintaining the representation ability. Experimental results on two applications: color constancy and image dehazing, demonstrate the superiority of our proposed network over the existing architectures, i.e., using 1/10 similar to 1/100 network parameters and computational cost while achieving comparable performance.

关键词： Point-wise Convolution statistical Regularity Color Constancy Haze Removal

来源：评论

学校读者我要写书评

暂无评论

Comparison of Higher Order statistical Method for Low Contrast images

Comparison of Higher Order Statistical Method for Low Contra...

引用

2018 International conference on Applied Electromagnetics, Signal processing and Communication, AESPC 2018

作者： Maji, Sourav Rout, Nirmal Kumar KIIT University School of Electronics Engineering Bhubaneswar India

ISBN: (纸本)9781538683330

Contrast enhancement and brightness preservation are widely used in different application of image processing. Histogram equalization (HE) is a common methods used for contrast enhancement as it is easy to implement for any digital images. But this method is not suitable for electronics application because it introduce unnecessary visual artifacts in the output images. To overcome the visual artifacts several segmentation methods are introduced for contrast enhancement. The two segmentation based on image enhancement algorithms, called Root-Mean-Skewness Bi-histogram Equalization (RMSKBHE)[8] and DUO-Histogram Equalization(DUO-HE)[9] gives the general idea or shape of the histogram of images. In this paper both the RMSKBHE and DUO-HE algorithm are proposed for better contrast enhancement of asymmetric input image and to find better contrast enhancement and brightness preserving for output image. The comparison of RMSKBHE and DUO-HE algorithms have been carried out using different quality measurement technique i.e. peak signal to noise ratio (PSNR) and absolute modified mean brightness error (AMMBE). Visual perception and statistical values for the DUO-HE algorithm is found out better than the RMSKBHE algorithm. © 2018 IEEE.

关键词： Luminance

来源：评论

学校读者我要写书评

暂无评论

Reconstruction of 3D porous media using multiple-point statistics based on a 2D training image

Reconstruction of 3D porous media using multiple-point stati...

引用

SPE Europec featured at 80th EAGE conference and Exhibition 2018

作者： Wu, Yuqi Lin, Chengyan Ren, Lihua Tian, Weichao Wang, Yang Zhang, Yimin China University of Petroleum China

Macroscopic transport properties of porous media essentially rely on the geometry and topology of their pore space. The premise of predicting these transport properties is to construct an accurate 3D pore space. To date the methods of modeling porous media are divided into two main groups, direct measurements by some equipment and stochastic statistical methods. Direct measurements of pore structure can be acquired with current equipment such as X-ray computed tomography and laser scanning confocal microscopy, but the unavailability of the equipment and the high cost of the measurement make their widespread application impossible. Many stochastic statistical methods, such as truncated Gaussian random field and simulated annealing methods, reconstruct 3D porous media based on some 2D thin sections by means of lower-order statistical functions. However these functions cannot reproduce the long-range connectivity of pore structure. Therefore, this paper will present a stochastic technique of reconstructing 3D pore space using multiple-point statistics with the purpose of solving the proposed problems. The single normal equation simulation algorithm (SNESIM), one of the most common methods for discrete variable simulation in multiple-point statistics, is the main tool to reproduce the long-range feature of pore space. To test the method, Berea sandstone was used as a sample. In the simulation process, a 2D thin section was taken as the training image for providing patterns of pore structure and some pixels were extracted from it as the conditioning data. The models were reconstructed using the SNESIM algorithm that serves as the simulation engine. In order to test the accuracy of these reconstructed models, pore geometry and topology and transport properties of the reconstructed models were compared with those of the real model obtained by X-ray computed tomography scanning. The comparison result shows that the reconstructed models are good agreement with the real model

关键词： Pore structure

来源：评论

学校读者我要写书评

暂无评论

A Study of Data Augmentation for Handwritten Character Recognition Using Deep Learning 16

A Study of Data Augmentation for Handwritten Character Recog...

引用

16th International conference on Frontiers in Handwriting Recognition (ICFHR)

作者： Hayashi, Taihei Gyohten, Keiji Ohki, Hidehiro Takami, Toshiya Oita Univ Fac Sci & Technol Oita Japan

ISBN: (纸本)9781538658758

While convolutional neural networks have made significant achievements in the field of handwriting recognition in recent years, large amounts of training data are required to obtain satisfactory results. To prepare large amounts of image data for training without increased labor, there is a way of increasing the number of images by applying general image processing methods, so-called data augmentation. However, it is difficult to generate character images like those written by different people and to overcome the problems related to the lack of training data by using conventional data augmentation methods. In this paper, we propose a method of acquiring the probability distribution of the features related to the character structure and generating character images of various handwritings using the probability distribution. The proposed method obtains statistical character structure models composed of probability distributions of strokes by learning from character image data. By generating strokes based on the probability distribution of each stroke and assembling them into a character, it becomes possible to generate character images of various handwriting samples not influenced by the original images. In the comparative experiments of handwritten character recognition with a convolutional neural network, good results could be obtained using not only conventional data augmentation methods but also the proposed method together.

关键词： character recognition deep learning data augmentation statistical character structure model

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473页 << < 99 100 101 102 103 104 105 106 107 108 > >>

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：