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检索条件"主题词=detection Algorithms"

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Auxiliary-vector detection on measured radar data

Auxiliary-vector detection on measured radar data

引用

IEEE National Conference on Radar

作者： George N. Karystinos Dimitris A. Pados Stella N. Batalama John D. Matyjas Department of Electronic and Computer Engineering Technical University of Crete Chania Greece Department of Electrical Engineering State University of New York University at Buffalo Buffalo NY USA Air Force Research Laboratory Rome NY USA

Derived from statistical conditional optimization criteria, the auxiliary-vector (AV) detection algorithm starts from the target vector and adding non-orthogonal auxiliary vector components generates an infinite sequence of tests that converges to the ideal matched filter (MF) processor for any positive definite input autocorrelation matrix. When the input autocorrelation matrix is replaced by a conventional sample-average estimate, the algorithm effectively generates a sequence of estimators of the ideal matched filter that offer exceptional bias/covariance balance for any given finite-size observation data record. In this work, the AV algorithm is evaluated on collected airborne phased-array radar data from the MCARM program and is seen to outperform in probability of detection (for any given false alarm rate) all known and tested adaptive detectors (for example AMF, generalized likelihood ratio test, the multistage Wiener filter algorithm, etc.).

关键词： Radar detection Radar measurements Testing Matched filters Autocorrelation Covariance matrix Phase detection detection algorithms Airborne radar Detectors

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Decomposition of branching volume data by tip detection

Decomposition of branching volume data by tip detection

引用

IEEE International Conference on Image Processing

作者： Wei Ma Bo Xiang Xiaopeng Zhang Hongbin Zha Key Laboratory of Machine Perception (Ministry of Education) Peking University China LIAMA-NLPR CAS Institute of Automation China

We present an approach to decomposing branching volume data into sub-branches. First, a metric is proposed for evaluating local convexities in volumetric data, and it is a criterion for global selection of tip points. Second, a multi-path growing strategy is adopted to segment the volumes based on a DFS transformation starting from the tips. Experiments show that this approach is capable of generating desirable components and reasonable segmentation boundaries of a volume.

关键词： Computer vision detection algorithms Shape Skeleton Data mining Face detection Laboratories Content addressable storage Automation Computer graphics

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Rotated Profile Signatures for robust 3D feature detection

Rotated Profile Signatures for robust 3D feature detection

引用

International Conference on Automatic Face and Gesture Recognition

作者： Timothy C. Faltemier Kevin W. Bowyer Patrick J. Flynn Progeny Systems Corporation Manassas VA USA Department of Computer Science and Engineering University of Notre Dame Notre Dame IN USA

While recent years have seen progress in face recognition from 3D images, nonfrontal head pose is still a challenge to existing techniques. We introduce a new system for 3D face recognition that is robust to facial pose variation. Large degrees of facial pose variation may lead to a significant fraction of the features visible in frontal images being occluded. High accuracy automatic feature and pose detection is performed by a new technique called rotated profile signatures (RPS). Experiments are performed on the largest available database of 3D faces acquired under varying pose. This database contains over 7,300 total images of 406 unique subjects gathered at the University of Notre Dame. Experimental results show that the RPS detection algorithm is capable of performing nose detection with greater than 96.5% accuracy across the pose variation represented in the data set used.

关键词： Robustness Computer vision Nose Face detection Face recognition Image databases Spatial databases Head detection algorithms Cameras

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Endmember detection using the Dirichlet process

Endmember detection using the Dirichlet process

引用

International Conference on Pattern Recognition

作者： Alina Zare Paul D. Gader Department of Computer and Information Science and Engineering University of Florida

ISBN: (纸本)9781424421749

An endmember detection algorithm for hyperspectral imagery using the Dirichlet process to determine the number of endmembers in a hyperspectral image is described. This algorithm provides an estimate of endmember spectra, proportion maps, and the number of endmembers needed for a scene. Updates to the proportion vector for a pixel are sampled using the Dirichlet process. As opposed to previous methods that prune unnecessary endmembers, the proposed algorithm is initialized with one endmember and new endmembers are added through sampling as needed. Results are shown on a two-dimensional dataset and a simulated dataset using endmembers selected from an AVIRIS hyperspectral image.

关键词： Hyperspectral imaging Hyperspectral sensors Pixel Layout Clustering algorithms Information science detection algorithms Image sampling Wavelength measurement Vectors

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Study on a detection algorithm for MIMO systems

Study on a detection algorithm for MIMO systems

引用

IEEE Asia-Pacific Conference on Circuits and Systems

作者： Ding Yuehua Yin Junxun School of Electronic and Information Engineering South China University of Technology Guangzhou China

In this paper, we present a detection algorithm for MIMO system with nonbinary modulation scheme. The proposed method is based on rectangular searching. It restricts the searching area to a certain rectangle when searching the candidate symbols for each symbol. It has considerably reduced computational complexity compared to ML (maximum likelihood) algorithm because only a small part of candidate constellation points are located in the searching rectangle. However, to our surprise, Simulation results show that the BER (bit error rate) performance of the proposed method outperforms the ML (maximum likelihood) algorithm when the SNR is between -10 dB and 15 dB. The reasons responsible for this unusual phenomena are also given.

关键词： detection algorithms MIMO Transmitting antennas Computational complexity Bit error rate Maximum likelihood detection Computational modeling Receiving antennas Transmitters Wireless communication

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Pitch detection Method for Noisy Speech Signals Based on Pre-Filter and Weighted Wavelet coefficients

Pitch Detection Method for Noisy Speech Signals Based on Pre...

引用

9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Ru-wei LI Chang-chun BAO Hui-jing DOU Speech and Audio Signal Processing Lab School of Electronic Information and Control EngineeringBeijing University of TechnologyBeijing 100124China

Most of the current pitch detection algorithms can not work well under the high noise *** this reason,a pitch detection algorithm for noisy speech signal based on pre-filtering and weighted wavelet coefficients is ***,the noisy speech signals are ***,the speech pre-filtered is decomposed by the quadratic spline ***,the wavelet coefficients of three consecutive scales are weighted to emphasize the sharp change ***,three candidate pitch periods are extracted from the weighted ***,the pitch period is calculated by autocorrelation *** show that this algorithm can increase the performance of pitch detection in noisy environment and decreases computational complexity compared with DWT-NCCF method.

关键词： Wavelet coefficients Working environment noise Wavelet transforms Signal processing algorithms Autocorrelation Speech analysis Filters Speech enhancement detection algorithms Spline

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Lane boundaries detection algorithm using vector lane concept

Lane boundaries detection algorithm using vector lane concep...

引用

International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Quoc Bao Truong Byung Ryong Lee Nam Geon Heo Young Jim Yum Jong Gook Kim Department of Mechanical and Automotive Engineering University of Ulsan Ulsan South Korea

A lane detection system is an important component of many intelligent transportation systems. In this paper, we present a robust and real-time lane tracking algorithm for any curved road. We use Non Uniform B-Spline (NUBS) interpolation method to construct the boundaries road lane. First, the Canny filter is employed to obtain edge map. Second, we apply parallel thinning algorithm into edge map to get the skeleton image. Once skeleton image is obtained, we introduce a new algorithm based on Vector Lane Concept to extract feature edge points that play the role as control points for NUBS interpolation process to represent left and right lane, separated. Finally, we estimate the curvature of left and right lane boundary for lane tracking. The result of this method can be used for Autonomous Guided Vehicles (AGV) system application.

关键词： detection algorithms Intelligent transportation systems Roads Interpolation Skeleton Robustness Spline Filters Image edge detection Feature extraction

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Traffic Anomaly detection at Fine Time Scales with Bayes Nets

Traffic Anomaly Detection at Fine Time Scales with Bayes Net...

引用

International Conference on Internet Monitoring and Protection, ICIMP

作者： Jeff Kline Sangnam Nam Paul Barford David Plonka Amos Ron Computer Science Department University of Wisconsin USA

Traffic anomaly detection using high performance measurement systems offers the possibility of improving the speed of detection and enabling detection of important, short-lived anomalies. In this paper we investigate the problem of detecting anomalies using traffic measurements with fine-grained timestamps. We develop a new detection algorithm (called S3) that utilizes a Bayes Net to efficiently consider multiple input signals and to explicitly define what is considered "anomalous''. The input signals considered by S3 are traffic volumes and correlations between ingress/egress packet and bit rates. These complementary signals enable identification of an expanded range of anomalies. Using a set of high precision traffic measurements collected at our campus border router over a 10 month period and an annotated anomaly log supplied by our network operators, we show that S3 is highly accurate, identifying 86% of the anomalies listed in the log. Compared with well known time series-based and wavelet-based detectors, this represents over a 20% improvement inaccuracy. Investigation of events identified by S3 that did not appear in the operator log indicate many are, in fact, true positives. Deployment of S3 in an operational environment supports this by showing zero false positives during initial tests.

关键词： Telecommunication traffic Detectors detection algorithms Bit rate Event detection Internet Monitoring Protection Measurement Signal processing

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Anomaly detection Support Vector Machine and Its Application to Fault Diagnosis

Anomaly Detection Support Vector Machine and Its Application...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Ryohei Fujimaki NEC Common Platform Software Research Laboratories

We address the issue of classification problems in the following situation: test data include data belonging to unlearned classes. To address this issue, most previous works have taken two-stage strategies where unclear data are detected using an anomaly detection algorithm in the first stage while the rest of data are classified into learned classes using a classification algorithm in the second stage. In this study, we propose anomaly detection support vector machine (ADSVM) which unifies classification and anomaly detection. ADSVM is unique in comparison with the previous work in that it addresses the two problems simultaneously. We also propose a multiclass extension of ADSVM that uses a pairwise voting strategy. We empirically present that ADSVM outperforms two-stage algorithms in application to an real automobile fault dataset, as well as to UCI benchmark datasets.

关键词： Fault detection Support vector machines Fault diagnosis Support vector machine classification detection algorithms Classification algorithms Voting Automobiles Benchmark testing Training data

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Vision-Based Road detection by Adaptive Region Segmentation and Edge Constraint

Vision-Based Road Detection by Adaptive Region Segmentation ...

引用

International Symposium on Intelligent Information Technology Application, IITA

作者： Yanqing Wang Deyun Chen Chaoxia Shi School of Computer Science and Technology Harbin University of Science and Technology Harbin Heilongjiang China School of Computer Science and Technology Nanjing University of Science and Technology of PLA Nanjing Jiangsu China

A novel vision-based road detection method was proposed in this paper to realize visual guiding navigation for ground mobile vehicles in outdoor environments. The road region was first segmented from the jumbled backgrounds by using an adaptive threshold segmentation algorithm named OTSU. Subsequently, the Canny edges extracted in grey images would be filtered in the road region so that the road boundary could be recognized accurately by reducing the unnecessary disturbances from the useless edge existed in background By combining the detection algorithm of both road region and road boundary, the road detection method proposed in this paper was robust against strong shadows, surface dilapidation and illumination variations. It has been tested on real ground mobile vehicle and performed well in real road environments.

关键词： Image edge detection Land vehicles Road vehicles Image segmentation Vehicle detection Navigation Image recognition detection algorithms Robustness Lighting

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