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检索条件"主题词=Detection algorithms"

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Early detection algorithms for 4×4 and 8×8 all-zero blocks in H.264/AVC

Early detection algorithms for 4×4 and 8×8 all-zero blocks...

引用

European Signal Processing Conference (EUSIPCO)

作者： Qin Liu Yiqing Huang Takeshi Ikenaga IPS Waseda University Kitakyushu Japan

ISBN: (纸本)9782839904506

H.264 is the latest HDTV video compression standard, which provides a significant improvement in coding efficiency at the cost of huge computation complexity. Provided that discrete cosine transform coefficient(DCT) blocks can be quantized to all zeros, the process of transform and quantization on this all-zero block(AZB) can be skipped, which will reduce significant redundant computations. In this paper, a theoretical analysis is performed for the sufficient condition for AZB detection. As a result, two partial sum of absolute differences (SAD) based 4×4 AZB detection algorithm are derived. Furthermore, a quantization parameter (QP) oriented 8×8 AZB detection algorithm is proposed according to the AZB's statistical analysis. Experimental results show that the proposed algorithms outperform the previous methods in all cases and achieve major improvement of computation reduction in the range from 12.16% to 42.68% for 4×4 transform, from 4.86% to 73.55% for 8×8 transform. The computation reduction increases as the QP increases.

关键词： Transforms Quantization (signal) Accuracy Upper bound detection algorithms Hardware Europe

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Towards designing secure in-vehicle network architectures using community detection algorithms

Towards designing secure in-vehicle network architectures us...

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IEEE Vehicular Networking Conference (VNC)

作者： Pierre Kleberger Nasser Nowdehi Tomas Olovsson Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Volvo Car Corporation Gothenburg Sweden

Efforts in securing the in-vehicle network have resulted in a number of proposed security mechanisms in recent years. However, so far little attention has been given to the actual architecture of the in-vehicle network. An approach within in-vehicle network design is to divide the network into domains, where each domain consists of a set of Electronic Control Units (ECUs) that handles some united functionality, e.g., body control, powertrain, and telematics. Still, this approach is based on “best engineering practice” and there is room for improvements. In this paper, we study real traffic from a modern car and we try to divide the in-vehicle network into domains using automated partitioning algorithms. To find the optimum division, we select four community detection algorithms, known from social network analysis, and we evaluate their ability to find these domains. We conclude that community detection algorithms can be used to identify in-vehicle domains based on the message types (signals) used in the in-vehicle network and we demonstrate this by applying the algorithms to real data. The approach is not limited to only message types, but domains can also be identified based on other criteria, such as frequency of messages, payload sizes, or Automotive Safety Integrity Levels (ASILs). We also conclude that the identification of good domains can facilitate the implementation of security measures. Therefore, we believe that the approach has great potential to help engineers in deriving secure in-vehicle network architectures during the design of a vehicle.

关键词： Communities Vehicles Security Partitioning algorithms detection algorithms Image edge detection Algorithm design and analysis

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Development of Lane and Zebra Crossing Marker detection algorithms

Development of Lane and Zebra Crossing Marker Detection Algo...

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Device Intelligence, Computing and Communication Technologies, (DICCT), International Conference on

作者： Vivek Chamoli R Gowri V P Dubey Jyoti Kandpal Jyoti Joshi Divesh Kumar Dept. of Electronics & Communication Engineering Graphic Era Hill University Dehradun India Dept. of Comupter Science & Engineering Graphic Era Hill University Dehradun India

This research involves using an object recognition system and an ancillary image sensor to detect lane markers and zebra crossings on a roadway in a vehicle. To perform this detection, these steps have been followed: take a picture of the scene, digitize it, normalize it, define a search area within it, look for lane and zebra markers within it. The Lane Tracking for Driving System was created to assist drivers in making lane departure decisions, to lessen concentration breaks, and to avoid accidents while driving. To offer a way to detect a specific traffic violation—namely, stopping on a zebra crossing at a traffic signal rather than following behind it—and to offer a workaround. In the proposed work, systems are implemented and improved using adaptive algorithms. MATLAB’s image processing toolbox is used to design and implement the proposed algorithm.

关键词： Image sensors Image processing Adaptive algorithms Communications technology Object recognition detection algorithms Vehicles

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Converting Output Scores from Outlier detection algorithms into Probability Estimates

Converting Output Scores from Outlier Detection Algorithms i...

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IEEE International Conference on Data Mining (ICDM)

作者： Jing Gao Pang-ning Tan Department of Computer Science and Engineering Michigan State University East Lansing MI USA

Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into well-calibrated probability estimates is more favorable for several reasons. First, the probability estimates allow us to select the appropriate threshold for declaring outliers using a Bayesian risk model. Second, the probability estimates obtained from individual models can be aggregated to build an ensemble outlier detection framework. In this paper, we present two methods for transforming outlier scores into probabilities. The first approach assumes that the posterior probabilities follow a logistic sigmoid function and learns the parameters of the function from the distribution of outlier scores. The second approach models the score distributions as a mixture of exponential and Gaussian probability functions and calculates the posterior probabilites via the Bayes' rule. We evaluated the efficacy of both methods in the context of threshold selection and ensemble outlier detection. We also show that the calibration accuracy improves with the aid of some labeled examples.

关键词： detection algorithms Calibration Logistics Computer science Bayesian methods Support vector machines Support vector machine classification State estimation Probability Costs

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Spatial Outlier detection algorithms Based on Knowledge Discovery

Spatial Outlier Detection Algorithms Based on Knowledge Disc...

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International Conference on Management and Service Science, MASS

作者： Jiang Bo

This paper proposes spatial outliers detection method of studying multiple non-spatial attributes based on special objects. SOFMF algorithm is presented and its implementation has been discussed in detail in this article. Simultaneously analyze and summarize this algorithm: overcome the insufficiency of many clustering algorithms, be able to find clusters in different shapes, be non-sensitive to the input data sequence, process noise data and multi-dimensional data well, and have multi-resolution. A novel idea for spatial data clustering is proposed by the author, emphatically numerous experiments prove this idea can be applied to spatial clustering quite well.

关键词： detection algorithms Neurons Clustering algorithms Spatial databases Data mining Topology Graph theory Testing Scattering Computer science

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Lattice Reduction Based detection algorithms in High Correlated MIMO-OFDM System

Lattice Reduction Based Detection Algorithms in High Correla...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Xiaojia Lu Pirkka Silvola Markku Juntti Centre for Wireless Communications University of Oulu Finland

The lattice reduction (LR) aided detectors for multiple-input multiple-output (MIMO) systems have been shown to have a better performance than conventional linear detectors like zero forcing (ZF) or minimum mean square (MMSE) detectors. In this paper, we study the performance of the LR aided detectors for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems in spatially correlated fading channels. Also, the computational complexity of the LR based linear detectors is studied with comparison to the conventional detectors. The simulation results show that the LR aided detectors are more robust to the spatial correlation than the conventional linear detectors and also have a low computational complexity close to the conventional linear detectors

关键词： Lattices detection algorithms Detectors MIMO Quadrature amplitude modulation Computational complexity OFDM modulation Maximum likelihood detection Fading Maximum likelihood decoding

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Bit-Wise detection algorithms for V-BLAST Systems

Bit-Wise Detection Algorithms for V-BLAST Systems

引用

IEEE Conference on Wireless Communications and Networking

作者： Guoquan Lu He Wang Yongyu Chang Xin Zhang Dacheng Yang Wireless Theories and Technologies Laboratory (WT&T) Beijing University of Posts and Telecommunications Beijing China

The Vertical Bell Laboratories Layered Space-Time (V-BLAST) scheme achieves very high spectral efficiency while maintaining low implementation complexity. There have been great efforts focusing on the V-BLAST detection algorithms. However, all these algorithms concentrate on the symbol-wise detection. In this paper, a bit-wise V-BLAST detection algorithm is proposed based on the fact that the bits in one modulation symbol may have different reliabilities depending on their mapping methods. This new algorithm regards bit, rather than symbol in traditional algorithms, as the minimum process unit to do the interference nulling, canceling and ordering. Considerable performance gains are achieved over the symbol-wise detection algorithms, which are demonstrated by simulations. Also, two simplified algorithms are proposed to reduce the computation complexity.

关键词： detection algorithms Receiving antennas Transmitting antennas Interference cancellation Computational modeling Maintenance MIMO Signal to noise ratio Communications Society Helium

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Investigating execution-characteristics of feature-detection algorithms

Investigating execution-characteristics of feature-detection...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jakob Danielsson Marcus Jägemar Moris Behnam Mikael Sjödin Mölardalen University Västeras Sweden Ericsson AB Stockholm Sweden

We discuss how to obtain information of execution characteristics, such as parallelizability and memory utilization, with the final aim to improve the performance and predictability of feature and corner detection algorithms for use in e.g. robotics and autonomous machines. Our aim is to obtain a better understanding of how computer vision algorithms use hardware resources and how to improve the time predictability and execution time of such algorithms when executing on multi-core CPUs. We evaluate a fork-join model applicable to feature detection algorithms and present a method for measuring how well the algorithm performance correlates with hardware resource usage. We have applied our method to the Featured from Accelerated Segment Test (FAST) algorithm. Our characterization of FAST reveals that it is an algorithm with excellent parallelism opportunities, resulting in an almost linear speed-up per core. Our measurements also reveal that the performance of FAST correlates very little with the number of misses in the L1 data cache, L1 instruction cache, data translation lookaside buffer and L2 cache. Thus, the FAST algorithm will not have a negative effect on the execution time when the input data fits in the L2 cache.

关键词： Feature extraction Prediction algorithms Hardware detection algorithms Velocity measurement Monitoring

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Evaluation of Performance of Several Established Pitch detection algorithms in Pathological Voices

Evaluation of Performance of Several Established Pitch Detec...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Seung-Jin Jang Seong-Hee Choi Hyo-Min Kim Hong-Shik Choi Young-Ro Yoon Department of biomedical engineering College of Health & Science Yonsei University South Korea Division of Otolaryngology-Head and Neck Surgery Department of Surgery University of Wisconsin Madison WI USA Department of Otolaryngology College of Medicine Yonsei University South Korea

Robust pitch estimation is important in many areas of speech processing. In voice pathology, diverse statistics extracted form pitch estimation were commonly used to test voice quality. In this study, we compared several established pitch detection algorithms (PDAs) for verification of adequacy of the PDAs. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices. Pitch errors of all PDAs used in this study more or less showed some changes between pathological and normal voices. According to the results of pitch errors, gross pitch error showed some increases in cases of pathological voices; especially excessive increase in PDA based on nonlinear time-series. In an analysis of types of pathological voices classified by aperiodicity and the degree of chaos, the more voice has aperiodic and chaotic, the more growth of pitch errors increased. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.

关键词： detection algorithms Pathology Personal digital assistants Testing Speech analysis Chaos Robustness Speech processing Statistical analysis Databases

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A quantitative methodology for analyzing the performance of detection algorithms

A quantitative methodology for analyzing the performance of ...

引用

International Conference on Computer Vision (ICCV)

作者： T. Kanungo M.Y. Jaisimha J. Palmer R.M. Haralick Department of Electrical Engineering University of Washington Seattle WA USA Department of Psychology University of Washington Seattle WA USA

The authors present a methodology for designing experiments to characterize detection algorithms. The usual method is to vary parameters of the input images or parameters of the algorithms and then construct operating curves that relate the probability of misdetection and false alarm for each parameter setting. Such an analysis does not integrate the performance of the numerous operating curves. A methodology is outlined for summarizing many operating curves into a few performance curves. This methodology is adapted from the human psychophysics literature and is general to any detection algorithm. The central concept is to measure the effect of variables in terms of the equivalent effect of a critical signal variable. The methodology is demonstrated by comparing the performance of two line detection algorithms.< >

关键词： Performance analysis Algorithm design and analysis detection algorithms Image edge detection Psychology Humans Computer vision Silicon compounds Design methodology Testing

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