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

16 篇 会议
2 篇 期刊文献
1 册 图书

馆藏范围

19 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

14 篇 工学
- 8 篇 计算机科学与技术...
- 6 篇 信息与通信工程
- 6 篇 软件工程
- 3 篇 光学工程
- 3 篇 电气工程
- 3 篇 电子科学与技术（可...
- 2 篇 机械工程
- 2 篇 仪器科学与技术
- 2 篇 控制科学与工程
- 1 篇 化学工程与技术
- 1 篇 生物工程
- 1 篇 安全科学与工程
9 篇 理学
- 7 篇 数学
- 5 篇 统计学（可授理学、...
- 3 篇 物理学
- 1 篇 生物学
- 1 篇 系统科学
4 篇 管理学
- 3 篇 图书情报与档案管...
- 1 篇 管理科学与工程(可...

主题

3 篇 databases
2 篇 mixtures
1 篇 mixture models
1 篇 query processing
1 篇 noise reduction
1 篇 information syst...
1 篇 content based re...
1 篇 support vector m...
1 篇 semantic segment...
1 篇 database systems
1 篇 indexing
1 篇 radar polarimetr...
1 篇 three-dimensiona...
1 篇 image segmentati...
1 篇 target tracking
1 篇 complexity class...
1 篇 signal processin...
1 篇 gold
1 篇 pixel
1 篇 extended kalman ...

机构

2 篇 multimedia signa...
1 篇 multimedia signa...
1 篇 japan assoc. for...
1 篇 dept. of elec. a...
1 篇 ece department r...
1 篇 vis. technol. gr...
1 篇 multimedia commu...
1 篇 tsinghua univers...
1 篇 dept. of elec. a...
1 篇 image formation ...
1 篇 multimedia signa...
1 篇 multimedia signa...
1 篇 massachusetts in...
1 篇 swiss institutes...
1 篇 dept. of compute...
1 篇 inrs-telecommuni...
1 篇 department of co...
1 篇 beckman inst. ad...
1 篇 computer vision ...
1 篇 university of il...

作者

5 篇 gunsel bilge
3 篇 bilge gunsel
3 篇 b. gunsel
2 篇 ulker yener
1 篇 zhanyu ma
1 篇 shin chajin
1 篇 ying chu
1 篇 cai yiyang
1 篇 hui zheng
1 篇 kim taeoh
1 篇 han yu
1 篇 koray kayabol
1 篇 yufei zha
1 篇 rajagopalan a.n.
1 篇 timofte radu
1 篇 zeng yu
1 篇 bätz michel
1 篇 maier andreas k.
1 篇 s. kubiz
1 篇 icoglu oguz

语言

19 篇 英文

检索条件"机构=Multimedia Signal Processing and Pattern Recognition Lab."

共 19 条记录，以下是1-10 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：

Wami Object Tracking Using L1 Tracker Integrated with a Deep Detector 25

Wami Object Tracking Using L1 Tracker Integrated with a Deep...

引用

25th IEEE International Conference on Image processing, ICIP 2018

作者： Onur Ozyurt, Erdem Gunsel, Bilge Multimedia Signal Proc. and Pattern Recognition Lab. Istanbul Technical University Turkey

ISBN: (纸本)9781479970612

We propose an object tracking method for Wide Area Motion Imagery (WAMI) video sequences, which models the tracking as a regularization problem through sparse representation of aerial video content. The proposed object tracker, Ll Dpct, applies particle filter tracking, and unlike the existing methods, it integrates a deep-learning-based object detector into the regularization scheme to improve the tracking performance. In order to enhance robustness to occlusion and scale changes, Ll Dpct monitors the state propagation, the level of sparsity as well as the representation capability of the model and receives feedback from the detector to update the observation model of the particle filter. Ll Dpct incrementally updates the dictionary of the sparse representation that enables us to efficiently represent the appearance changes of the object arising from illumination changes and high motion. Numerical results obtained on commonly used VIVID and UAV123 datasets denote that Ll Dpct significantly improves the object tracking performance in terms of precision rate and success rate compared to the state-of-the-art trackers. © 2018 IEEE.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Robust audio watermark decoding by nonlinear classification

Robust audio watermark decoding by nonlinear classification

引用

13th European signal processing Conference, EUSIPCO 2005

作者： Kirbiz, S. Yaslan, Y. Günsel, B. Multimedia Signal Processing and Pattern Recognition Lab. Dept. of Electronics and Communications Eng. Istanbul Technical University 34469 Istanbul Turkey

ISBN: (纸本)1604238216

This paper introduces an audio watermark (WM) decoding scheme that performs a Support Vector Machine (SVM) based supervised learning followed by a blind decoding. The decoding process is modelled as a two-class classification procedure. Initially, wavelet decomposition is performed on the training audio signals, and the decomposed audio frames watermarked with +1 and -1 constitute the training sets for Class 1 and Class 2, respectively. The developed system enables to extract embedded WM data at lower than -40dB Watermark-to-signal- Ratio (WSR) levels with more than 95% accuracy and it is robust to degradations including audio compression (MP3, AAC), and additive noise. It is shown that the proposed audio WM decoder eliminates the drawbacks of correlation-based methods.

关键词： Additive noise

来源：评论

学校读者我要写书评

暂无评论

A multiple model structure for tracking by variable rate particle filters

A multiple model structure for tracking by variable rate par...

引用

作者： Ulker, Yener Gunsel, Bilge Kirbiz, Serap Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University Dep. of Electronics and Communications Engineering 34469 Maslak Istanbul Turkey

ISBN: (纸本)9781424421756

In contrast to the fixed rate modeling of the conventional methods, recently introduced variable rate particle filters (VRPF) achieves to track maneuvering objects with a small number of states by imposing a probability distribution on state arrival times. Although this enables VRPF an appealing method, representing the target motion dynamics with a single model hinders the capability of estimating maneuver parameters precisely. To overcome this weakness we have incorporated multiple model approach with the variable rate model structure. The introduced model referred as Multiple Model Variable Rate Particle Filter (MM-VRPF) utilizes a parsimonious representation for smooth regions of trajectory while it adaptively locates frequent state points at high maneuver regions, resulting in a much more accurate tracking. Simulation results obtained in a bearings-only target tracking problem show that the proposed model outperforms the conventional VRPF, the fixed rate multiple model particle filters (MMPF) and interacting multiple model using extended Kalman filters (IMM-EKF). © 2008 IEEE.

关键词： Extended Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Incremental non-negative matrix factorization for dynamic background modelling

Incremental non-negative matrix factorization for dynamic ba...

引用

7th International Workshop on pattern recognition in Information Systems PRIS 2007;In Conjunction with ICEIS 2007

作者： Bucak, Serhat S. Gunsel, Bilge Gursoy, Ozan Multimedia Signal Processing and Pattern Recognition Lab. Dept. of Electronics and Comm. Eng. Istanbul Technical University 34469 Maslak Istanbul Turkey

ISBN: (纸本)9789728865931

In this paper, an incremental algorithm which is derived from Non-negative Matrix Factorization (NMF) is proposed for background modeling in surveillance type of video sequences. The adopted algorithm, which is called as Incremental NMF (INMF), is capable of modeling dynamic content of the surveillance video and controlling contribution of the subsequent observations to the existing representation properly. INMF preserves additive, parts-based representation, and dimension reduction capability of NMF without increasing the computational load. Test results are reported to compare background modeling performances of batch-mode and incremental NMF in surveillance type of video. Moreover, test results obtained by the incremental PCA are also given for comparison purposes. It is shown that INMF outperforms the conventional batch-mode NMF in all aspects of dynamic background modeling. Although object tracking performance of INMF and the incremental PCA are comparable, INMF is much more robust to illumination changes.

关键词： Non-negative matrix factorization

来源：评论

学校读者我要写书评

暂无评论

An ensemble based incremental learning framework for concept drift and class imbalance

An ensemble based incremental learning framework for concept...

引用

2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Ditzler, Gregory Polikar, Robi ECE Department Rowan University Signal Processing and Pattern Recognition Lab. Glassboro NJ 08028 United States

ISBN: (纸本)9781424469178

We have recently introduced an incremental learning algorithm, Learn ++.NSE, designed to learn in nonstationary environments, and has been shown to provide an attractive solution to a number of concept drift problems under different drift scenarios. However, Learn++.NSE relies on error to weigh the classifiers in the ensemble on the most recent data. For balanced class distributions, this approach works very well, but when faced with imbalanced data, error is no longer an acceptable measure of performance. On the other hand, the well-established SMOTE algorithm can address the class imbalance issue, however, it cannot learn in nonstationary environments. While there is some literature availab.e for learning in nonstationary environments and imbalanced data separately, the combined problem of learning from imbalanced data coming from nonstationary environments is underexplored. Therefore, in this work we propose two modified frameworks for an algorithm that can be used to incrementally learn from imbalanced data coming from a nonstationary environment. © 2010 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

SAR IMAGE CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTURES

SAR IMAGE CLASSIFICATION WITH NORMALIZED GAMMA PROCESS MIXTU...

引用

IEEE International Conference on Image processing

作者： Koray Kayabol Bilge Gunsel Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University

ISBN: (纸本)9781479923427

We propose a novel image prior for the non-parametric Bayesian mixture model based unsupervised classification of SAR images. We modified the Normalized Gamma Process prior that constitutes a more general form of the Dirichlet Process prior in order to enclose the contribution of the adjacent pixels into the classification scheme. This yields an image classification prior embedded in a mixture model that allows infinite number of clusters and enables reaching to smoothed classification maps. Based on the classification results obtained on synthetic and real TerraSAR-X images, it is shown that the proposed model is capable of accurately classifying the pixels. It applies a simple iterative update scheme at a single run without performing a hierarchical clustering strategy as used in the previously proposed methods. It is also demonstrated that the model order estimation accuracy of the proposed method outperforms the conventional finite mixture models.

关键词： Infinite mixture models Normalized gamma process mixtures Nonparametric Bayesian Image classification SAR images Image classification Mixture models images Radar polarimetry classification scheme pixel Rescue Synthetic aperture radar Specific absorption rate SAFETY ANALYSIS REPORTS mixtures

来源：评论

学校读者我要写书评

暂无评论

Classification and indexing of paintings based on art movements 12

Classification and indexing of paintings based on art moveme...

引用

12th European signal processing Conference, EUSIPCO 2004

作者： Icoglu, Oguz Gunsel, Bilge Sariel, Sanem Multimedia Signal Processing and Pattern Recognition Lab. Electrical-Electronics Eng. Faculty Istanbul Technical University Maslak-Istanbul34469 Turkey Vienna University of Technology Building Physics and Human Ecology Institute Austria

ISBN: (纸本)9783200001657

This paper outlines the automatic extraction of features of paintings' art movements such as classicism, impressionism and cubism;and introduces a system developed for the classification and indexing of paintings based on their art movements. A six dimensional feature set is proposed for the representation of content and it is shown that the feature set enables to highlight art movements efficiently. In the classifier design, statistical pattern recognition approach is exploited and Bayesian, k-NN and SVM classifiers are employed. A classification accuracy of over 90% is achieved with very small false alarm ratios while the lowest performance is obtained by the k-NN. System also offers a quick query based database search by indexing the paintings with their six dimensional feature vectors, and provides an applicable program for museums and exhibition centres. © 2004 EUSIPCO.

关键词： Query processing

来源：评论

学校读者我要写书评

暂无评论

A boosting discriminative model for moving cast shadow detection

引用

6th International Conference on Energy Minimization Methods in Computer Vision and pattern recognition, EMMCVPR 2007

作者： Yufei, Zha Ying, Chu Duyan, Bi Signal and Information Processing Lab. Engineering College of Air Force Engineering University xi'an China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)9783540741954

Moving cast shadow causes serious problem while segmenting and extracting foreground from image sequences, due to the misclassification of moving shadow as foreground. This paper proposes a boosting discriminative model for moving cast shadow detection. Firstly, color invariance subspace and texture invariance subspace are obtained by the color and texture difference between current image and background image;then, boosting is selected based on theses subspaces to discriminate cast shadow from moving objects;finally, temporal and spatial coherence of shadow and foreground is employed on Discriminative Random Fields for accurate image segmentation through graph cut. Results show that the proposed method excels classical method both in indoor and outdoor scene. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Image analysis

来源：评论

学校读者我要写书评

暂无评论

A PERCEPTUALLY ENHANCED BLIND SINGLE-CHANNEL AUDIO SOURCE SEPARATION BY NON-NEGATIVE MATRIX FACTORIZATION

A PERCEPTUALLY ENHANCED BLIND SINGLE-CHANNEL AUDIO SOURCE SE...

引用

European signal processing Conference

作者： S. Kubiz B. Gunsel Multimedia Signal Processing and Pattern Recognition Lab. Istanbul Technical University Dept. of Electronics and Communications Engineering

This paper proposes a 2D Non-negative Matrix Factorization (NMF) based single-channel source separation algorithm that emphasizes perceptually important components of audio. Unlike the existing methods, the proposed scheme performs a psychoacoustic pre-processing on the mixture spectrogram in order to suppress audio components that are not critical to human hearing sensation while amplifying the perceptually important ones. This yields the auditory spectrogram referred as sonogram of the observed audio mixture and the individual sources are then extracted by 2D NMF. Test results reported in terms of signal-to-Distortion-Ratio (SDR), signal-to-Inference-Ratio (SIR) and signal-to-Artifact-Ratio (SAR) show that the proposed perceptually enhanced separation improves the quality of decomposed audio sources by 1.5-6.5 dB with a reduced computational complexity.

关键词： Audio matrix decomposition Sonogram factorization complexity classes Spectrogram NMF protocol

来源：评论

学校读者我要写书评

暂无评论

WAMI OBJECT TRACKING USING L_1 TRACKER INTEGRATED WITH A DEEP DETECTOR

WAMI OBJECT TRACKING USING L_1 TRACKER INTEGRATED WITH A DEE...

引用

IEEE International Conference on Image processing

作者： Erdem Onur Ozyurt Bilge Gunsel Multimedia Signal Proc. and Pattern Recognition Lab. Istanbul Technical University Turkey

We propose an object tracking method for Wide Area Motion Imagery (WAMI) video sequences, which models the tracking as a regularization problem through sparse representation of aerial video content. The proposed object tracker, L1Dpct, applies particle filter tracking, and unlike the existing methods, it integrates a deep-learning-based object detector into the regularization scheme to improve the tracking performance. In order to enhance robustness to occlusion and scale changes, L1Dpct monitors the state propagation, the level of sparsity as well as the representation capability of the model and receives feedback from the detector to update the observation model of the particle filter. L1Dpct incrementally updates the dictionary of the sparse representation that enables us to efficiently represent the appearance changes of the object arising from illumination changes and high motion. Numerical results obtained on commonly used VIVID and UAV123 datasets denote that L1Dpct significantly improves the object tracking performance in terms of precision rate and success rate compared to the state-of-the-art trackers.

关键词： Target tracking Detectors Dictionaries Object tracking Monitoring Minimization

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2页 << < 1 2 > >>

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：