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检索条件"主题词=Detection algorithms"

共 7324 条记录，以下是111-120 订阅

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Bit-plane extension to a class of intensity-based corner detection algorithms

Bit-plane extension to a class of intensity-based corner det...

引用

European Signal Processing Conference (EUSIPCO)

作者： Ambar Dutta Animesh Mandal B. N. Chatterji Avijit Kar Department of Computer Science & Engineering Jadavpur University Kolkata India Department of Computer Science & Engineering B.P.P.LM.T. Kolkata India Department of Computer Engineering B.I.T. Mesra at Kolkata Kolkata India Jadavpur University Kolkata West Bengal IN

Corners are important image features whose detection is very important in many computer vision tasks. In this paper we have evaluated the performance of five intensity based corner detectors with the help of a dozen test images, artificial and real, based on six performance measures of which three are proposed by us. We then propose a new approach, using bitplane decomposition, in which a grayscale image is first divided into several bit-planes, and then the original corner detectors are applied on all the bit-planes simultaneously and finally using a threshold, all the higher bit-plane corners are recombined up to the thresholded bit-plane to obtain the final set of corners. Using this approach, we have seen that the performance of the algorithms has improved significantly with respect to both detection and time.

关键词： Roads Signal processing algorithms detection algorithms Detectors Gray-scale Computer vision Europe

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Comparing Community detection algorithms on Neuroimaging Data from Multiple Subjects

Comparing Community Detection Algorithms on Neuroimaging Dat...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Joshua De Souza Fumihiko Taya Nitish V. Thakor Anastasios Bezerianos Singapore Institute Neurotechnology National University of Singapore Singapore SG Singapore Institute Neurotechnology National University of Singapore Singapore

It is well-known that the brain is a complex network""brain areas dedicated to different functions. As such,""consisting of""it is natural to shift toward brain network from brain mapping for deeper understanding of brain functions. Although graph theoretical network metrics measuring global or local properties of network topology have been used to investigate the brain network, they do no provide any information about intermediate scale of the brain network, which is provided by the community structure analysis.""In this paper, we propose a method to compare different community detection algorithms for multiple subjects data in terms of the agreement of a group-based community structure with individual community structures. As it is crucial to find a single group-based community structure for a group of subjects to discuss about brain areas and connections, a number of algorithms based on different approaches have been proposed. To show the feasibility of the method for comparing different algorithms, two community detection algorithms based on different approaches ("virtual-typical-subject" and "group analysis") were examined. The Normalized Mutual Information was computed to measure similarity between the group-based community structure and individual community structures derived from resting-state fMRI functional network, and was used for comparing the two algorithms. Our method demonstrated that the algorithm based on the group-analysis approach detected a group-based community structure with greater agreement with individual community structures.

关键词： detection algorithms Brain Neuroimaging Correlation Periodic structures Mutual information Indexes

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Robust detection algorithms for Time Reversal Matched Field Processing

Robust Detection Algorithms for Time Reversal Matched Field ...

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Amir Asif Qian Bai Department of Computer Science and Engineering York University Toronto ONT Canada

To explain super resolution focusing achieved in time reversal, matched field processing (TR/MFP), an analytical multipath model based on geometric optics approximation with strong total internal reflections was presented in A. Asif and Q. Bai, (2006). This paper uses the multipath model to derive the system response matrix in TRTMFP and exploits the structure of the response matrix to develop detection algorithms for determining the number and locations of passive targets embedded in a random medium. Experimental results prove the accuracy of the algorithms in detecting passive targets

关键词： Robustness detection algorithms Optical scattering Analytical models Transducers Signal processing algorithms Algorithm design and analysis Solid modeling Geometrical optics Optical signal processing

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Comparison of ship detection algorithms in spaceborne SAR imagery

Comparison of ship detection algorithms in spaceborne SAR im...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Peng Chen Weigen Huang Jingsong Yang Bin Fu Xiulin Lou Aiqing Shi Laboratory of Ocean Dynamic Processes and Satellite Oceanography Scripps Institution of Oceanography Hangzhou China

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Comparison of Pulsed Sinusoid Radio Frequency Interference detection algorithms Using Time and Frequency Sub-Sampling

Comparison of Pulsed Sinusoid Radio Frequency Interference D...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Sidharth Misra Christopher Ruf Department of Atmospheric Oceanic and Space Sciences University of Michigan Ann Arbor MI USA

The performance of two major Radio Frequency Interference (RFI) detection algorithms is compared. The peak detection algorithm and the kurtosis detection algorithm are characterized using the receiver operating characteristic (ROC) for pulsed sinusoid RFI. Downlink data bandwidth is one of the major design factors to be considered when comparing detection algorithms. Results are presented in this paper that compare the kurtosis algorithm performance with an ideally matched peak detection algorithm. The RFI parameters are also varied to analyze the overall detection performance of both algorithms. Factors such as implementation details, resource usage, post-processing and practicality are also addressed for both algorithms.

关键词： Radiofrequency interference detection algorithms Frequency Radiometers Bandwidth Detectors Signal resolution Algorithm design and analysis Hardware Receivers

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Some comparisons among several pitch detection algorithms

Some comparisons among several pitch detection algorithms

引用

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

作者： M. Cheng L. Rabiner A. Rosenberg C. McGonegal Bell Laboratories Murray Hill NJ USA

A comparative performance study of seven pitch detection algorithms was conducted. A speech data base, consisting of eight utterances spoken by 3 males, 3 females, and 1 child was constructed. Telephone, close talking microphone, and wideband recordings were made of each of the utterances. For each of the utterances in the data base a "standard" pitch contour was semiautomaticallly measured using a highly sophisticated interactive pitch detection program. The "standard" pitch contour was then compared with the pitch contour that was obtained from each of the seven programmed pitch detectors. The algorithms used in this study were (1) a center clipping, infinite-peak clipping, modified autocorrelation method, (2) the cepstral method, (3) the SIFT method, (4) the parallel processing time domain method, (5) the data reduction method, (6) a spectral flattening LPC method, and (7) the AMDF method. A set of measurements was made on the pitch contours to quantify the various types of errors which occur in each of the above methods. Included among the error measurements were the average and standard deviation of the error in pitch period during voiced regions, the number of gross errors in the pitch period, and the number of voiced-unvoiced classification errors. For each of the error measurements, the individual pitch detectors could be rank ordered as a measure of their relative performance as a function of recording condition, and pitch range of the various speakers. Results are presented on rankings based on one category of errors.

关键词： detection algorithms Measurement standards Detectors Speech Telephony Microphones Wideband Autocorrelation Cepstral analysis Parallel processing

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Static community detection algorithms for evolving networks

Static community detection algorithms for evolving networks

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International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Thomas Aynaud Jean-Loup Guillaume LIP6/CNRS-Université Pierre et Marie Curiee Paris France

Complex networks can often be divided in dense sub-networks called communities. Using a partition edit distance, we study how three community detection algorithms transform their outputs if the input network is slightly modified. The instabilities appear to be important and we propose a modification of one algorithm to stabilize it and to allow the tracking of the communities in an evolving network. This modification has one parameter which is a tradeoff between stability and quality. The resulting algorithm appears to be very effective. We finally use it on an evolving network of blogs.

关键词： detection algorithms Stability Partitioning algorithms Blogs Complex networks IP networks Computer networks Physics computing Web pages Social network services

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Performance evaluation of V-BLAST detection algorithms and a novel segmented detection algorithm

Performance evaluation of V-BLAST detection algorithms and a...

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IEEE Conference on Vehicular Technology (VTC)

作者： Bo Gui Daiming Qu Department Electron. & Information Engineering Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)0780382552

Several detection algorithms for the vertical Bell Laboratories layered space time (V-BLAST) system are compared. We propose the concept of segmented detection on the observation that the overall performance of decision feedback equalization (DFE) is limited by the performance of the first detected subchannel. We perform maximum-likelihood (ML) detection for the first several subchannels and use the DFE procedure to detect the remaining subchannels. Also, we propose a novel segmented detection algorithm based on the minimum mean square error (MMSE) criterion. Compared with DFEs, segmented detection improves the detection performance with little increase of complexity. Computer simulation verifies it.

关键词： detection algorithms Decision feedback equalizers MIMO Receiving antennas Space technology Maximum likelihood detection Mean square error methods Computer simulation Transmitting antennas Interference suppression

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Estimating network parameters for selecting community detection algorithms

Estimating network parameters for selecting community detect...

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International Conference on Information Fusion

作者： Leto Peel Advanced Technology Centre BAE Systems Bristol UK

This paper considers the problem of algorithm selection for community detection. The aim of community detection is to identify sets of nodes in a network which are more interconnected relative to their connectivity to the rest of the network. A large number of algorithms have been developed to tackle this problem, but as with any machine learning task there is no “one-size-fits-all” and each algorithm excels in a specific part of the problem space. This paper examines the performance of algorithms developed for weighted networks against those using unweighted networks for different parts of the problem space (parameterised by the intra/inter community links). It is then demonstrated how the choice of algorithm (weighted/unweighted) can be made based only on the observed network.

关键词： Communities Classification algorithms Prediction algorithms Algorithm design and analysis Mutual information Machine learning algorithms detection algorithms

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A Regularized Least Squares-Based Method for Optimal Fusion of Speech Pitch detection algorithms

A Regularized Least Squares-Based Method for Optimal Fusion ...

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International Conference of Signal Processing and Intelligent Systems (ICSPIS)

作者： Ziba Imani Seyed Jahanshah Kabudian Department of Computer Engineering and Information Technology Razi University Kermanshah Iran

ISBN: (纸本)9781728111957;9781728111940

Fundamental frequency estimation is one of the most important issues in the field of speech processing. An accurate estimate of the fundamental frequency plays a key role in the field of speech and music analysis. So far, various methods have been proposed in the time- and frequency-domain. However, the main challenge is the strong noises in speech signals. In this paper, to improve the accuracy of fundamental frequency estimation, we propose a method for optimal combination of fundamental frequency estimation methods, in noisy signals. In this method, to discriminate voiced frames from unvoiced frames in a better way, the Voiced/Unvoiced (V/U) scores of four pitch detection methods are combined linearly. These methods are: Autocorrelation, Yin, YAAPT and SWIPE. After identifying the Voiced/Unvoiced label of each frame, the fundamental frequency (F 0 ) of the frame is estimated using the SWIPE method. The optimal coefficients for linear combination are determined using the regularized least squares method with Tikhonov regularization. To evaluate the proposed method, 10 speech files (5 female and 5 male voices) are selected from the PTDB-TUG standard database and the results are presented in terms of SDFPE, GPE, VDE, PTE and FFE standard error criteria. The results indicate that our proposed method relatively reduced the aforementioned criteria (averaged in various SNRs) by 27.13%, 22.14%, 17.40% and 26.74% respectively, which demonstrate the effectiveness of the proposed method in comparison to state-of-the-art methods.

关键词： Mathematical model Estimation detection algorithms Training Frequency estimation Noise measurement Standards

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