检索结果-内蒙古大学图书馆

PROTOTYPING IDTV FUNCTIONS USING PGAS

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1990年第3期36卷 296-300页

作者： RANTANEN, H NIEMINEN, A Research Department Nokia Consumer Electronics Limited Tampere Finland

The utilization of user-programmable gate arrays (PGAs) to build a TV prototype is discussed. Two IDTV prototypes have been constructed in which some image processing algorithms (e.g. interpolation, motion detection, and video signal filtering) have been implemented by PGAs. The PGAs have enabled fast prototype building and testing of various algorithms on the same printed circuit board. Only a memory device must be reprogrammed to change the action of the PGA chip. After algorithms have been implemented and tested by PGAs, they are easily implementable by ASIC (application-specific integrated circuits) technology.< >

关键词： Prototypes HDTV Electronics packaging Circuit testing change detection algorithms Application specific integrated circuits TV Image processing Filtering algorithms Interpolation

来源：评论

学校读者我要写书评

暂无评论

Introduction to the Issue on Distributed Processing in Vision Networks

引用

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2008年第4期2卷 445-447页

作者： Aghajan, Hamid Kleihorst, Richard Rinner, Bernhard Wolf, Wayne Stanford Univ Dept Elect Engn Stanford CA 94305 USA NXP Semicond Res Eindhoven Netherlands Klagenfurt Univ Klagenfurt Austria Georgia Inst Technol Atlanta GA 30332 USA

Distributed vision networks is a multidisciplinary topic that interfaces the fields of computer vision, signal processing, pervasive computing, embedded programming, wireless sensor networks, and ambient intelligence. It creates opportunities for design paradigm shifts in these fields through emphasizing distributed vision processing and collaborative fusion of information over the network. In this premise, novel smart environment applications can be envisioned that are scalable, real-time, adaptive, interpretive, context-aware, and user-centric in nature.

关键词： Distributed processing Collaboration Signal processing algorithms Digital cameras Sensor fusion Smart cameras Target tracking change detection algorithms Wireless sensor networks Image sensors

来源：评论

学校读者我要写书评

暂无评论

A NEW METHOD FOR STUDYING SOME STATISTICAL FAILURE-detection ALGORITHM

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1993年第1期38卷 114-116页

作者： DECAMBRY, O ESIEE Noisy le Grand France

In this note, we describe a class of dynamical algorithms for detecting a change of parameter in a statistical model. Using large deviation results, we approximate the expected time between false alarms. We also approximate the expected time delay for failure detection. These approximations provide a criterion to measure the delay for detection, which is easily computable within the whole class.

关键词： detection algorithms change detection algorithms Heuristic algorithms Delay effects Detectors Testing Statistical analysis Stochastic processes Fluctuations Random variables

来源：评论

学校读者我要写书评

暂无评论

change detection using the object features

Change detection using the object features

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Irmgard Niemeyer Prashanth Reddy Marpu Sven Nussbaum TU Bergakademie Freiberg Institute of Mine-Surveying and Geodesy Freiberg Germany Systems Analysis and Technology Evaluation Institute of Energy Research Research Centre Juelich Julich Germany

For the detection of changes, several statistical techniques exist. When adopted to high-resolution imagery, the results of the traditional pixel-based algorithms are often limited. Especially if small structural changes are to be detected, object- based procedures show promises. In the given paper, we propose an unsupervised object-based change detection and change classification approach based on the object features. Following the automatic pre-processing, image objects and their object features are extracted. change detection is performed by the multivariate alteration detection (MAD), accompanied by the maximum autocorrelation factor (MAF) transformation. The change objects are then classified using the fuzzy maximum likelihood estimation (FMLE). Finally the classification of changes is improved by probabilistic label relaxation.

关键词： Object detection Image segmentation Pixel Feature extraction Data mining Layout Eigenvalues and eigenfunctions change detection algorithms Shape measurement Geodesy

来源：评论

学校读者我要写书评

暂无评论

change detection in Climate Data over the Iberian Peninsula

Change Detection in Climate Data over the Iberian Peninsula

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Raquel Sebastião Pedro Pereira Rodrigues João Gama LIAAD-INESC Porto L.A. & Faculty of Science University of Porta Porto Portugal LIAAD-INESC Porto L.A. & Faculty of Science & Faculty of Medicine University of Porta Porto Portugal

This paper addresses the space-time change detection problem in climate data over the Iberian Peninsula using a 50 years dataset. The data were analyzed concerning the temporal and geographical information, using the following methodology: information about space-time drifts in climate data was obtained by applying a change detection algorithm on all the temporal data available for each physical location considered in this study; the performance and the robustness of this algorithm were then assessed by the McNemar nonparametric statistical test on cluster structures; geographical correlations were inferred using visualization tools and graphical representations of data. Most of the space-temporal drifts detected by the algorithm were confirmed by the results of the McNemar test and are in accordance with visual and graphical representations, supporting the advantage of using inter-disciplinary methods. This analysis also shows that there are locations which do not reveal any change along all the observed years.

关键词： change detection algorithms Clustering algorithms Testing Data analysis Information analysis Performance analysis Algorithm design and analysis detection algorithms Robustness Data visualization

来源：评论

学校读者我要写书评

暂无评论

Multiple-model tracking for the detection of lane change maneuvers

Multiple-model tracking for the detection of lane change man...

引用

IEEE Symposium on Intelligent Vehicle

作者： K. Weiss N. Kaempchen A. Kirchner Electronic Research Department Volkswagen Ag Wolfsburg Germany Department of Measurement Control and Microtechnology University of Ulm (EBS) Ulm Germany

Volkswagen research has developed a system for vehicle surround perception which integrates different sensor data of the environment into a combined description by using a single model Kalman tracker. This paper deals with the extension of the tracking system by means of an interacting multiple-model algorithm (IMM) to improve the tracking stability during curves and to detect lane changes of the observed target vehicle. The applied IMM-tracker uses specialized models for lateral and longitudinal motion that are partly affected by curvature estimation. The technique is tested with recorded sequences of measurement data and shows robust tracking and well-fitting classification of the dynamical behavior of the targets.

关键词： Target tracking Sensor phenomena and characterization Sensor systems Kalman filters change detection algorithms Stability Vehicle detection Motion estimation Testing Robustness

来源：评论

学校读者我要写书评

暂无评论

An adaptive multiscale approach to unsupervised change detection in multitemporal SAR images

An adaptive multiscale approach to unsupervised change detec...

引用

IEEE International Conference on Image Processing

作者： F. Bovolo L. Bruzzone Department of Information and Communication Technologies University of Trento Trento Italy

A novel adaptive multiscale approach to unsupervised change detection in multitemporal synthetic aperture radar (SAR) images is proposed. This approach is based on a multiresolution decomposition of the log-ratio image (obtained by a comparison of a pair of co-registered images acquired at different times on the same area) in a set of scale-dependent images characterized by a different trade-off between speckle reduction and preservation of geometrical details. For each pixel to be analyzed, a sub-set of reliable scales is identified according to an automatic local analysis of the statistic of the data. The final change-detection map is obtained according to an adaptive scale-driven fusion algorithm, which properly exploits the results of the analysis at different scales for producing an accurate and reliable change-detection map in both homogeneous and border areas. Experimental results confirm the effectiveness of the proposed technique.

关键词： Radar detection Synthetic aperture radar Speckle Image analysis change detection algorithms Algorithm design and analysis Remote sensing Image motion analysis Satellites Image sensors

来源：评论

学校读者我要写书评

暂无评论

A change detection Algorithm for High Resolution Remote Sensing Images based on Data Analysis

A Change Detection Algorithm for High Resolution Remote Sens...

引用

Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Tao Liu Bohan Zhang College of Computer Science and Technology Heilongjiang Institute of Technology Harbin China School of Information Engineering China University of Geosciences Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

With the development of remote sensing technology to high resolution, high resolution remote sensing images are widely used in change detection. This paper uses Convolutional Neural Network (CNN) as its core model. The first step is data preprocessing, including data cutting, re-projection and normalization. Then the output of post-processing and change model is refined by threshold processing and morphological operation. Experiments show that the maximum detection time of CNN is only 400 milliseconds, showing higher speed performance. In terms of detection accuracy, the best CNN accuracy rate is 96.6%, and the worst CNN accuracy rate is 72.3%. The highest accuracy rates of RNN and SVM are 69.4% and 67.3%, respectively. As far as the reliability of detection is concerned, CNN has the best reliability, which is 96.9%, RNN is 79% and SVM is 72.2%. These results show that CNN can achieve better performance in typical high-resolution remote sensing image change detection tasks.

关键词： Support vector machines Accuracy Data analysis change detection algorithms Data preprocessing Data enhancement Data models Convolutional neural networks detection algorithms Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Shot change detection with adaptive thresholds

Shot change detection with adaptive thresholds

引用

IEEE International Workshop on VLSI Design and Video Technology, IWVDVT

作者： Min Zhi An-Ni Cai School of Telecommunications Engineering Beijing University of Posts and Telecommunications Beijing China School of Computer Inner Mongolia Normal University Hohhot China

ISBN: (纸本)0780390059

Shot change detection is one of the critical techniques in video browsing and indexing system. In this paper, we propose a shot change detection algorithm with adaptive thresholds on DC images. The bit-rate information is used to decrease the number of I frames that take part in the shot change detection. Then, local adaptive thresholds are obtained based on the main color of a segment of the video sequence. Finally, shot changes are detected based on modified twin-comparison method. Experimental results show that our algorithm can detect shot change detection from long video sequence with reduced computation complexity, and at the same time solve the problems caused by object moving and camera panning in the shot change detection.

关键词： Gunshot detection systems Object detection Video sequences Video compression change detection algorithms Indexing detection algorithms Image segmentation Cameras Statistics

来源：评论

学校读者我要写书评

暂无评论

Object-Based change detection in Satellite Images Combined with Neural Network Autoencoder Feature Extraction

Object-Based Change Detection in Satellite Images Combined w...

引用

Workshops on Image Processing Theory, Tools and Applications, IPTA

作者： Ekaterina Kalinicheva Jérémie Sublime Maria Trocan ISEP - LISITE laboratory DaSSIP team Issy-Les-Moulineaux France

change detection is a challenging task in the field of remote sensing. While most applications use supervised change detection and classification techniques, it still remains a difficult task to create a training database for generic applications. In this paper, we propose an end-to-end unsupervised change detection and clustering baseline. The presented baseline firstly deploys a neural network autoencoder for feature extraction and comparison to detect some meaningful changes. These changes are further segmented with 3D graph-based techniques and clustered. The presented algorithm gives promising results and is fully unsupervised.

关键词： Feature extraction Image segmentation Three-dimensional displays Image reconstruction change detection algorithms Clustering algorithms Satellites

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：