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

36 篇 会议
4 篇 期刊文献

馆藏范围

40 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

26 篇 工学
- 22 篇 电气工程
- 4 篇 计算机科学与技术...
- 3 篇 软件工程
- 2 篇 光学工程
25 篇 理学
- 22 篇 物理学
- 4 篇 数学
- 2 篇 统计学（可授理学、...

主题

8 篇 neural networks
6 篇 image processing
6 篇 stochastic proce...
5 篇 neurons
5 篇 magnetorheologic...
5 篇 image segmentati...
5 篇 signal processin...
5 篇 statistical mode...
4 篇 binary data
4 篇 image restoratio...
4 篇 data modeling
4 篇 statistical anal...
3 篇 computer science
3 篇 algorithms
3 篇 algorithm develo...
3 篇 radon
3 篇 machine learning
3 篇 image classifica...
3 篇 error analysis
3 篇 detection and tr...

机构

2 篇 syracuse univ.
2 篇 texas tech univ.
1 篇 purdue univ.
1 篇 département imag...
1 篇 international co...
1 篇 northwestern uni...
1 篇 lebanese amer un...
1 篇 inst space sci b...
1 篇 univ. of sydney
1 篇 univ. of chicago
1 篇 purdue universit...
1 篇 nccosc rdt and e...
1 篇 univ leicester u...
1 篇 univ massachuset...
1 篇 lockheed palo al...
1 篇 univ autonoma yu...
1 篇 univ calif los a...
1 篇 naval command co...
1 篇 univ. of central...
1 篇 univ. montpellie...

作者

2 篇 krishnaswamy d
2 篇 abatzoglou theag...
2 篇 abatzoglou tj
1 篇 gervasi osvaldo
1 篇 chen ct
1 篇 bedini l
1 篇 roska t
1 篇 chen shiuh-yung
1 篇 reagan john t.
1 篇 lavalle steven m...
1 篇 avadhanam n
1 篇 liu y
1 篇 bilbro gl
1 篇 mehrotra k
1 篇 phoha vir v.
1 篇 oldham wjb
1 篇 balaram j
1 篇 hutchinson seth ...
1 篇 zhu sc
1 篇 faurous p

语言

29 篇 英文
11 篇 其他

检索条件"任意字段=Neural and Stochastic Methods in Image and Signal Processing II 1993"

共 40 条记录，以下是11-20 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：

STORING TEMPORAL SEQUENCES OF PATTERNS IN neural NETWORKS 2

STORING TEMPORAL SEQUENCES OF PATTERNS IN NEURAL NETWORKS

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： KRISHNASWAMY, D MEHROTRA, K MOHAN, CK RANKA, S Syracuse Univ. (United States)

ISBN: (纸本)0819412813

This paper presents neural network models for storing terminating and cyclic temporal sequences of patterns under synchronous, sequential and asynchronous dynamics. We use fully interconnected neural networks with asymmetric weight connections for synchronous and sequential dynamics and a layered neural network with feedback for asynchronous dynamics. The network were successfully implemented and the number of patterns that could be stored and recalled was approximately 12% of the size of the patterns in the network.

关键词： Neurons neural networks Interference (communication) Brain Content addressable memory Network architectures Argon Artificial neural networks Control systems Information science

来源：评论

学校读者我要写书评

暂无评论

ROBUST FRACTAL CHARACTERIZATION OF 1-D AND 2-D signalS 2

ROBUST FRACTAL CHARACTERIZATION OF 1-D AND 2-D SIGNALS

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： AVADHANAM, N MITRA, S Texas Tech Univ. (United States)

ISBN: (纸本)0819412813

Fractal characterization of signals is well suited in analysis of some time series data and in classification of natural shapes and textures. A maximum likelihood estimator is used to measure the parameter H which is directly related to the fractal dimension. The robustness of the estimator and the performance of the method are demonstrated on datasets generated using a variety of techniques. Finally the characterization is used in segmentation of composite images of natural textures.

关键词： Fractal analysis image segmentation Composites Error analysis Statistical analysis image classification Polymers Edge detection Computer vision technology Machine vision

来源：评论

学校读者我要写书评

暂无评论

CLASSIFICATION OF PEN GESTURES USING LEARNING VECTOR QUANTIZATION 2

CLASSIFICATION OF PEN GESTURES USING LEARNING VECTOR QUANTIZ...

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： SHANKAR, RV KRISHNASWAMY, D Syracuse Univ. (United States)

ISBN: (纸本)0819412813

This paper deals with the classification of pen gestures using the learning vector quantization algorithm, a supervised learning technique. Both single stroke and multi stroke gestures are considered. The slope information from the strokes is extensively preprocessed before classification. The preprocessing and the classification algorithms chosen help to obtain very high rates of gesture classification. This is especially true in the multi stroke case. The recognition of the pen gestures is independent of their position, orientation, and size.

关键词： Quantization Detection and tracking algorithms Machine learning Distance measurement neural networks Vector spaces Feature extraction Information science Tablets Visualization

来源：评论

学校读者我要写书评

暂无评论

EXPLICIT NOISE HYPOTHESES IN SPEECH RECOGNITION 2

EXPLICIT NOISE HYPOTHESES IN SPEECH RECOGNITION

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： FOX, R JOSEPHSON, J Univ. of Texas Pan American (United States) The Ohio State Univ. (United States)

ISBN: (纸本)0819412813

Noise is typically present in the input signal for perception problems. Noise arises in speech recognition due to both background sounds, and unintentional derivations from the intended utterance on the part of the speaker. The task of speech recognition is to correctly identify the words (or meaning) carried by the speech signal. Thus the speech recognizer must be able to successfully handle noise. We describe here a method of explicitly identifying and labeling noise elements in a speech signal. NOISE hypotheses are generated, and considered for acceptance, as part of an abductive inference strategy for speech processing. An abductive problem solver is able to treat noise within a unified inferential framework, treating noise hypotheses similarly to other hypotheses, weighing the explanatory alternatives in a context-sensitive manner, and with no need to resort to indirect methods to achieve noise tolerance.

关键词： Speech recognition Interference (communication) signal processing Composites Tongue Laser induced plasma spectroscopy Acoustics Data modeling neural networks Statistical modeling

来源：评论

学校读者我要写书评

暂无评论

TRAINING A BOLTZMANN MACHINE FOR EDGE-PRESERVING image-RESTORATION 2

TRAINING A BOLTZMANN MACHINE FOR EDGE-PRESERVING IMAGE-RESTO...

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： BEDINI, L PANDOLFI, S TONAZZINI, A Istituto di Elaborazione della Informazione (Italy)

ISBN: (纸本)0819412813

The most successful methods to stabilize inverse ill-posed problems in visual reconstruction use a priori information on the local regularity of the image as well as constraints on the geometry of the discontinuities. A commonly used method to incorporate prior knowledge into the problem is to adopt a Bayesian approach in which the image is modelled by a parametric Gibbs prior and the solution is obtained by minimizing the resulting posterior energy function (MAP estimate). However, this approach presents two major difficulties: the first is related to the non-convexity of the function to be optimized; the second to the choice of the model parameters that best fit the available prior knowledge. Since these parameters strongly affect the quality of the reconstructions, their selection is a critical task. They are usually determined empirically by trial and error. The paper proposes a generalized Boltzmann Machine which makes it possible to learn the most appropriate parameters for a given class of images from a series of examples. The trained Boltzmann Machine is then used to implement an annealing scheme for the minimization of the non-convex posterior energy. The method is applied to the restoration of piecewise smooth images.

关键词： Neurons Chemical elements image restoration stochastic processes Expectation maximization algorithms signal processing Binary data Magnetorheological finishing Annealing Visualization

来源：评论

学校读者我要写书评

暂无评论

methods FOR NUMERICAL-INTEGRATION OF HIGH-DIMENSIONAL POSTERIOR DENSITIES WITH APPLICATION TO STATISTICAL image-MODELS 2

METHODS FOR NUMERICAL-INTEGRATION OF HIGH-DIMENSIONAL POSTER...

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： LAVALLE, SM MORONEY, KJ HUTCHINSON, SA Univ. of Illinois/Urbana-Champaign (United States)

ISBN: (纸本)0819412813

Numerical computation with Bayesian posterior densities has recently received much attention both in the statistics and computer vision communities. This paper explores the computation of marginal distributions for models that have been widely considered in computer vision. These computations can be used to assess homogeneity for segmentation, or can be used for model selection. In particular, we discuss computation methods that apply to a Markov random field formation, implicit polynomial surface models, and parametric polynomial surface models, and present some demonstrative experiments.

关键词： image segmentation Visual process modeling Data modeling Monte Carlo methods Statistical modeling Magnetorheological finishing Numerical integration Statistical analysis Computer vision technology Machine vision

来源：评论

学校读者我要写书评

暂无评论

image RECOVERY AND SEGMENTATION USING COMPETITIVE LEARNING IN A LAYERED NETWORK 2

IMAGE RECOVERY AND SEGMENTATION USING COMPETITIVE LEARNING I...

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： PHOHA, VV OLDHAM, WJB Univ. of Central Texas (United States) Texas Tech Univ. (United States)

ISBN: (纸本)0819412813

In this study, the principle of competitive learning is used to develop an iterative algorithm for image recovery and segmentation. Within the framework of Markov Random Fields, the image recovery problem is transformed to the problem of minimization of an energy function. A local update rule for each pixel point is then developed in a stepwise fashion and is shown to be a gradient descent rule for an associated global energy function. Relationship of the update rule to Kohonen's update rule is shown. Quantitative measures of edge preservation and edge enhancement for synthetic images are introduced. Simulation experiments using this algorithm on real and synthetic images show promising results on smoothing within regions and also on enhancing the boundaries. Restoration results computer favorably with recently published results using Markov Random Fields and mean field approximation.

关键词： image restoration Algorithm development image segmentation image processing algorithms and systems Magnetorheological finishing image enhancement image quality Computer science Reconstruction algorithms Ions

来源：评论

学校读者我要写书评

暂无评论

BAYESIAN PART TOLERANCING WITH MEASUREMENT UNCERTAINTY 2

BAYESIAN PART TOLERANCING WITH MEASUREMENT UNCERTAINTY

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： NOBLE, A MUNDY, J GE Corporate Research and Development Ctr. (United Kingdom) GE Corporate Research and Development Ctr. (United States)

ISBN: (纸本)0819412813

Gibbs sampling, and other stochastic simulation methods, have recently received considerable attention in Bayesian statistics. Significant progress has been made in the areas of developing techniques for sampling from non-conjugate distributions, and analyzing theoretical and practical aspects relating to convergence. One of the powers of Gibbs sampling is the way it can simplify the expression of data models by replacing the evaluation of the integrals needed to compute the relevant posterior quantities by sampling from multidimensional distributions. This has opened up the way to solve complex Bayesian models that are not analytically tractable. In this paper we show how to separate variability in model parameters from variability due to the model extraction process by fitting hierarchial models to image sequences using Gibbs sampling. First, we review some of the recent developments in Gibbs sampling. Then we describe some of our experimental work using Gibbs sampling to extract geometric parameter distributions from industrial images.

关键词： Statistical analysis Error analysis Tolerancing Manufacturing Statistical modeling image processing Process modeling image segmentation Visual process modeling Data modeling

来源：评论

学校读者我要写书评

暂无评论

STATISTICAL-MECHANICS APPROACH TO image DIFFERENCING BASED INSPECTION 2

STATISTICAL-MECHANICS APPROACH TO IMAGE DIFFERENCING BASED I...

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： BALARAM, J Jet Propulsion Lab. (United States)

ISBN: (纸本)0819412813

image differencing based inspection allows the comparison of a prior reference image with a subsequent inspection image to detect changes that can be attributed to flaw induced damage between inspection periods. In our application, the inspection system is required to find new flaws to orbiting space structures that might arise as a result of micro-meteorites, space debris, effects of atomic oxygen damage etc. Direct differencing of these `before' and `after' signals for the flaw detection problem is complicated by changes that are not the result of flaws. These benign changes result from the image noise, mis-registration effects induced by non- repeatability in the imaging viewpoint at each inspection period, and variability of ambient illumination resulting from change of solar angle induced by orbital motion. In this paper we discuss the methods by which some of these effects are handled and suggest a modeling framework using statistical mechanics techniques.

关键词： Inspection Mechanics Cameras Oxygen image registration Statistical modeling Ultraviolet radiation Fiber optic illuminators Wind energy signal detection

来源：评论

学校读者我要写书评

暂无评论

NEYMAN-PEARSON DETECTION FOR CSO processing 2

NEYMAN-PEARSON DETECTION FOR CSO PROCESSING

引用

CONF ON neural AND stochastic methods IN image AND signal processing 2

作者： ABATZOGLOU, TJ REAGAN, JT Lockheed Palo Alto Research Lab. (United States)

ISBN: (纸本)0819412813

This paper expands on previous research efforts for superresolving unresolved closely-space objects (CSO) present in IR focal plane data via model-based signal processing techniques. It has been shown that a model-based maximum likelihood estimation technique attains the Cramer-Rao theoretical lower bound on the source position and intensity and it is used for resolving unresolved targets. Here, we present a Neyman-Pearson log-likelihood ratio receiver structure for detecting the presence of a single unresolved target (non-CSO) versus the presence of two CSOs. We derive analytical expressions for the receiver operating characteristic (ROC) curves for the proposed receiver structure. For a given false alarm rate (i.e. declaring the presence of a two-source CSO scenario when a single-source non-CSO is present), the Neyman-Pearson receiver maximizes the probability of detection. With simulated two-source CSO data, we present a partial verification of the ROC curves.

关键词： Receivers signal to noise ratio Model-based design Probability theory Chlorine Sensors signal processing Mathematical modeling Data modeling Point spread functions

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4页 << < 1 2 3 4 > >>

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：