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检索条件"主题词=change detection algorithms"

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Fast shadow detection for urban autonomous driving applications

Fast shadow detection for urban autonomous driving applicati...

引用

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Sooho Park Sejoon Lim Computer Science and Artificial Intelligence Laboratory MIT Cambridge MA USA

This paper presents shadow detection methods for vision-based autonomous driving in an urban environment. Shadows misclassified as objects create problems in autonomous driving applications. Real-time efficient algorithms in dynamic background settings are proposed. Without the static background assumption, which was often used in previous work to develop fast algorithms, our scheme estimates the varying background efficiently. A combination of various features classifies each pixel into one of the following categories: road, shadow, dark object, or other objects. In addition to pixel level classification, spatial context is also used to identify the shadows. Our results show that our methods perform well for autonomous driving applications and are fast enough to work in real time.

关键词： Roads Image segmentation Layout Cameras Object detection Image edge detection Intelligent robots USA Councils Heuristic algorithms change detection algorithms

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12N test procedure for NPSF testing and diagnosis for SRAMs

12N test procedure for NPSF testing and diagnosis for SRAMs

引用

IEEE International Conference on Semiconductor Electronics (ICSE)

作者： R.R. Julie W.H. Wan Zuha R.M. Sidek Department of Electrical and Electronics Engineering University Putra Malaysia Malaysia

Testing and diagnosis techniques play a key role in the advance of semiconductor memory technologies. The challenge of failure detection has attracted investigation on efficient testing and diagnosis algorithm for better fault coverage and diagnostic resolution. March algorithms are widely used in SRAM testing to detect and diagnose SRAM fault model since they are relatively simple and yet providing high fault coverage and diagnostic resolution. In this case to achieve high fault coverage the structure of the consecutive memory backgrounds are very important. This paper aims to prove the efficiency of March 12N algorithm in term of detection and identification capability and locate the NPSF model fault. The details of test and diagnosis procedures for NPSF are demonstrated in this paper. The fault detection and diagnostic of the SRAM memories in this paper is verified and proven. The required march elements, detection requirement, detection conditions and fault syndromes are also enlightened. Furthermore, these particulars are required to determine a good algorithm other applications.

关键词： Random access memory Fault detection Fault diagnosis Test pattern generators Electronic equipment testing Algorithm design and analysis change detection algorithms Semiconductor device testing Semiconductor memory Electrical fault detection

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A singular values and singular vectors based blind multiuser detector

A singular values and singular vectors based blind multiuser...

引用

International Conference on Communication Technology (ICCT)

作者： Yang Heng Zhang Xianda State Key Laboratory of Intelligent Technology and System Department of Automation Tsinghua University Beijing China

A singular values and singular vectors blind multiuser detector is proposed in this paper. This detector uses singular values and singular vectors of signal subspace to get a linear MMSE multiuser detector for a DS-CDMA system. This method uses FAST (fast approximate subspace tracking) algorithm to estimate singular values and singular vectors. The multiuser detector proposed in this paper can converge quickly and its output can achieve high SNR.

关键词： Detectors Vectors Multiuser detection change detection algorithms Multiaccess communication Bit error rate Spread spectrum communication Gaussian noise Additive white noise Laboratories

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A practical method of road detection for intelligent vehicle

A practical method of road detection for intelligent vehicle

引用

IEEE International Conference on Automation and Logistics

作者： Dezhi Gao Wei Li Jianmin Duan Banggui Zheng College of Electronic Information & Control Engineering Beijing University of Technology Beijing China

ISBN: (纸本)9781424447947

In the paper, a practical method for road detection is proposed. Many features of vehicle are introduced to detect the preceding vehicles. According to the characteristics of lane marks and vehicles, the improved Sobel operator convolution kernel is introduced in the image preprocessing to enhance the robustness of the algorithm. In order to be feasible to the change of illumination and road conditions, the adaptive double threshold method is introduced to get the binary image, the edges which are needed during detection of lane marks and front vehicles are extracted with Hough Transformation and SUSAN algorithm based on adaptive threshold in different contrast ratio. In order to apply the information to implement the lane departure warming system and forward collision warming system, both distances from host vehicle to left and right lane lines and preceding vehicles are estimated according to the inverse projection. Experiment results indicate that this algorithm is feasible for different road conditions and can realize the detection and tracking of the lane lines and vehicles with robustness and efficiency simultaneously.

关键词： Vehicle detection Intelligent vehicles Robustness change detection algorithms Image edge detection Road vehicles Convolution Kernel Lighting Data mining

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An efficient algorithm for maintaining consistent group membership in ad hoc networks

An efficient algorithm for maintaining consistent group memb...

引用

International Conference on Distributed Computing Systems Workshop

作者： P. Pradhan A. Helal Computer and Information Science and Engineering Department University of Florida Gainesville FL USA

Designing a reliable group membership algorithm for mobile ad hoc networks is a non-trivial task since we must deal with limited device power, possibilities of frequent disconnections and network partitions. The function of the group membership service is to maintain a consistent group view across all members of the group. Only then can we say that the group membership service is reliable. Reliable group membership protocols in distributed systems (e.g., the virtual partitioning (VP) algorithm) make free use of aborts as a tactic to ensure the reliability of group formation. We present a group membership algorithm based on VP that minimizes message exchanges and thus reduces the power spent in transmission by detecting and eliminating superfluous aborts.

关键词： Intelligent networks Ad hoc networks Protocols Partitioning algorithms Maintenance Power system reliability Voting Power generation Batteries change detection algorithms

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Human Object Tracking Algorithm with Human Color Structure Descriptor for Video Surveillance Systems

Human Object Tracking Algorithm with Human Color Structure D...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Shao-yi Chien Wei-kai Chan Der-chun Cherng Jing-ying Chang Media IC and System Laboratory Graduate Institute of Electronics Engineering and Department of Electrical Engineering National Taiwan University Taipei Taiwan

Segmentation, tracking, and description extraction are important operations in smart camera surveillance systems. In this paper, a robust segmentation-and-descriptor based tracking algorithm is proposed. Segmentation is applied first, and description for each connected component is extracted for object classification to generate the video object masks. It can do segmentation, tracking, and description extraction with a single algorithm without redundant computation. In addition, a new descriptor for human objects, human color structure descriptor (HCSD), is also proposed for this algorithm. Experimental results show that the proposed algorithm can provide precise video object masks and trajectories. It is also shown that the proposed descriptor, HCSD, can achieve better performance than scalable color descriptor and color structure descriptor of MPEG-7 for human objects

关键词： Humans Video surveillance Smart cameras change detection algorithms Active contours Algorithm design and analysis Trajectory Indexing Robustness MPEG 7 Standard

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Real-time models supporting resource management decisions in highly variable systems

Real-time models supporting resource management decisions in...

引用

IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Sara Casolari Michele Colajanni Stefania Tosi Francesco Lo Presti Department of Computer Engineering University of Modena and Reggio Emilia and INFM Italy Department of Computer Engineering University of Roma Tor Vergata Italy

Data centers providing modern interactive applications are enriched by autonomous management decision systems that are able to clone and migrate virtual machines, to re-distribute resources or to re-map services in real-time. At the basis of all these decisions, there is the need of a continuous evaluation of the state of system resources and of detecting when some relevant changes are occurring. Unfortunately, the load of interactive applications reaching the system is intrinsically heterogeneous with consequent highly variable effects on the resource behavior emerging from system monitors. Hence, existing algorithms for online detection of state changes are affected by low precision and scarce robustness when they are applied to modern contexts. We propose a novel model for online detection of relevant state changes that combines a filtered representation of the raw measures with adaptive detection rules. Experiments carried out on real and emulated data sets confirm that the proposed model is able to timely signal all relevant state changes, to limit false detections and, even more important, its results are robust in highly variable contexts.

关键词： Time series analysis Adaptation model Context change detection algorithms Delay detection algorithms Data models

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Assessment of Feature Selection Techniques for Support Vector Machine Classification of Satellite Imagery

Assessment of Feature Selection Techniques for Support Vecto...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Tarek Habib Jordi Inglada Gregoire Mercier Jocelyn Chanussot GIPSA-Lab (Signal and Images Department) CNRS I. N. P. Grenoble France Centre national d'études spatiales (Cnes - DCT/SI/AP) Institut Telecom Telecom Bretagne / CNRS FRE 3167 LabSTICC/CID.

The problem of focusing on the most relevant information in a potentially overwhelming quantity of data has become increasingly important. Using irrelevant or noisy features not only can affect the accuracy of the classification results obtained but also the convergence time. In this paper several feature selection algorithms used with the Support Vector Machine (SVM) algorithm are presented. The feature selection algorithms are classified as filter and wrapper approaches. Two different wrapper techniques are presented: the first one uses the generalization error estimate of the leave-one-example-out error, while the second one uses the error estimate of the leave-one-feature-out error. Filter approaches with 4 different parameters are presented, namely: the mutual information, the FScore, and two advanced entropy measures are studied. Results in the context of change detection using satellite imagery are then discussed.

关键词： Support vector machine classification Support vector machines Filters Testing change detection algorithms Telecommunications Machine learning algorithms Kernel Artificial satellites Indium phosphide

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Edge strength evaluation with reaction-diffusion systems

Edge strength evaluation with reaction-diffusion systems

引用

International Conference on Image and Vision Computing New Zealand, IVCNZ

作者： Atsushi Nomura Makoto Ichikawa Koichi Okada Hidetoshi Miike Faculty of Education Yamaguchi University Yamaguchi Japan Faculty of Letters Chiba University Inage Chiba Japan Education Promotion Center Yamaguchi University Yamaguchi Japan Graduate School of Science and Engineering Yamaguchi University Ube Japan

The present paper proposes a reaction-diffusion algorithm that detects edge positions and evaluates their strength. Edge strength refers to the sharpness of spatial brightness change at an edge position in image brightness distribution. The authors previously found that a discretised system derived from the FitzHugh-Nagumo reaction-diffusion equations spontaneously organises pulses at edge positions and works as an edge detector for binary images. Although the previous system has a merit in that it can detect edges having sharp corners, it is not applicable to grey level images or edge strength evaluation. The proposed algorithm utilises multiple systems, each of which consists of two subsystems of the reaction-diffusion equations coupled with a diffusion equation. The diffusion equation modulates a parameter value of the reaction-diffusion equations and helps to evaluate a level of edge strength. In addition, there is a connection between the two subsystems in each system; the connection helps to eliminates pseudo-pulses organised in the subsystems. Integration of the outputs of the multiple systems provides edge strength distribution. Finally, we apply the proposed algorithm to test images and confirm its performance.

关键词： Image edge detection Brightness Stereo vision Chemicals Nonlinear equations Computer vision Systems engineering education Laplace equations Image segmentation change detection algorithms

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A Sinusoidal Model Approach to Acoustic Landmark detection and Segmentation for Robust Segment-Based Speech Recognition

A Sinusoidal Model Approach to Acoustic Landmark Detection a...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： T.N. Sainath T.J. Hazen MIT Computer Science and Artificial Intelligence Laboratory Cambridge MA USA

In this paper, we present a noise robust landmark detection and segmentation algorithm using a sinusoidal model representation of speech. We compare the performance of our approach under noisy conditions against two segmentation methods used in the SUMMIT segment-based speech recognizer, a full segmentation approach and an approach that detects segment boundaries based on spectral change. The word error rate of the spectral change segmentation method degrades rapidly in the presence of noise, while the sinusoidal and full segmentation models degrade more gracefully. However, the full segmentation method requires the largest computation time of the three approaches. We find that our new algorithm provides the best tradeoff between word accuracy and computation time of the three methods. Furthermore, we find that our model is robust when speech is contaminated by various noise types

关键词： Acoustic signal detection Speech recognition Acoustic noise Hidden Markov models Noise robustness Working environment noise Speech analysis Mathematical model change detection algorithms Error analysis

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