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检索条件"主题词=detection algorithms"

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Formant-based technique for automatic filled-pause detection in spontaneous spoken english

Formant-based technique for automatic filled-pause detection...

引用

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

作者： Kartik Audhkhasi Kundan Kandhway Om D. Deshmukh Ashish Verma Department of Electrical Engineering University of Southern California Los Angeles CA USA IBM India Research Laboratory New Delhi India

detection of filled pauses is a challenging research problem which has several practical applications. It can be used to evaluate the spoken fluency skills of the speaker, to improve the performance of automatic speech recognition systems or to predict the mental state of the speaker. This paper presents an algorithm for filled pause detection that is based on the premise that the vocal tract characteristics, and hence the formants, are stable during the production of a filled pause. The performance of the proposed algorithm is evaluated on real-life recordings of call center agents where the locations of the filled pauses are hand labeled. The proposed algorithm outperforms a standard cepstral stability based filled pause detection algorithm and a standard pitch-based detection technique.

关键词： Automatic speech recognition Cepstral analysis Acoustic signal detection Robust stability detection algorithms Natural languages Databases Acoustic measurements Gravity Frequency

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Threshold-free detection of maternal heart rate from abdominal electrocardiogram

Threshold-free detection of maternal heart rate from abdomin...

引用

IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

作者： M. Sheikh M. Algunaidi M.A. Mohd Ali Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia

This work is involved the threshold-free detection of QRS complexes in an abdominal electrocardiogram (AECG) waveform. The precision in the identification of QRS complexes is of great importance for on-line maternal heart rate calculation and, will lead to on line fetal heart detection. During the last century much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others, each of which has different effectiveness and weaknesses. Although their performance is generally good, but, the main weakness is that, they are threshold dependent. In the proposed algorithm a RR moving interval is calculated, based on normal maximum and minimum heart rate (HR). This has the advantage of ensuring that every R-peak is contained between the edges of the moving interval. Thus the effectiveness of this algorithm is that, it is threshold independent, and after every peak detection the RR moving interval is updated to calculate the next peak contained between its edges. The complete algorithm is implemented using MATLAB 7.4. The method is validated using 20 recorded data. The average sensitivity and average positive predictivity of the detection method are 99.05% and 99.8% respectively.

关键词： Heart rate detection Heart rate Abdomen Finite impulse response filter Cutoff frequency Band pass filters Neural networks detection algorithms Filtering algorithms Signal processing

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Distributed Spectrum Sensing with Two-Stage detection for Cognitive Radio

Distributed Spectrum Sensing with Two-Stage Detection for Co...

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IEEE Conference on Vehicular Technology (VTC)

作者： Yohannes D. Alemseged Chen Sun Ha Nguyen Tran Hiroshi Harada National Institute of Information and Communications Technology Yokosuka Japan

ISBN: (纸本)9781424425143

In this paper we investigate spectrum sensing for cognitive radio (CR) by using multiple spectrum sensors. We explore sensing schemes based on soft information combining, hard information combining and a two-stage detection scheme that uses both soft information combining and hard information combining. The two-stage detection scheme is shown to provide improved performance compared to sensing based on either hard information combining or soft information combining alone with a trade-off of sensing time. Computer simulation results are provided to validate the concept.

关键词： Cognitive radio Chromium Radio frequency Statistical distributions FCC Radiofrequency identification Signal detection detection algorithms AWGN Sun

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Group event detection for video surveillance

Group event detection for video surveillance

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Weiyao Lin Ming-Ting Sun Radha Poovendran Zhengyou Zhang Department of Electrical Engineering University of Washington Seattle USA Microsoft Research Microsoft Corporation Redmond USA

ISBN: (纸本)9781424438273

This paper presents a novel approach for automatic recognition of group activities for video surveillance applications. We propose to use a group representative to handle the recognition with flexible or varying number of group members, and use an asynchronous hidden Markov model (AHMM) to model the relationship between two people. Furthermore, we propose a group activity detection algorithm which can handle symmetric and asymmetric group activities, and demonstrate that this approach enables the detection of hierarchical interactions between people. Experimental results show the effectiveness of our approach.

关键词： Event detection Video surveillance Hidden Markov models Clustering algorithms Humans Sun detection algorithms Legged locomotion Terrorism Solids

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Boosting Twin Support Vector Machine Approach for MCs detection

Boosting Twin Support Vector Machine Approach for MCs Detect...

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Asia-Pacific Conference on Information Processing, APCIP

作者： Xinsheng Zhang School of Management Xi''an University of Architecture and Technology Xi'an China

Clustered microcalcifications (MCs) are one of the early signs of breast cancer, and they are of great importance for an early diagnosis. Moreover, the spatial distribution and the shape of the microcalcifications have a significant impact in medical practice to evaluate the probability of malignancy of the tumor. In this paper we investigate an approach based on boosted twin support vector (Boosting-TWSVM) for detection of microcalcifications clusters (MCs) in digital *** the algorithm, we formulate MCs detection as a supervised-learning problem and apply the trained Boosted-TWSVM classifier to develop the detection algorithm. We tested the proposed method using DDSM database of 80cases mammograms containing about 980 MCs. detection performance of the proposed method is evaluated by using receiver operating characteristic (ROC) curves. We compared the proposed algorithm with other existing methods. In our experiments, the proposed detection method outperformed the other methods tested. In particular, a sensitivity as high as 92.35% was achieved by our detection algorithm at an error rate of 8.3%. The experiment results suggest that Boosted-TWSVM is a promising technique for MCs detection.

关键词： Boosting Support vector machines detection algorithms Testing Breast cancer Shape Medical diagnostic imaging Breast neoplasms Clustering algorithms Delta-sigma modulation

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A performance investigation of coded MC-CDM with the Chase detection algorithm

A performance investigation of coded MC-CDM with the Chase d...

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

作者： B. Badic Amar H. Kabashi R. M. Joyce T. O'Farrell School of Engineering Swansea University Swansea UK School of Electronic & Electrical Engineering University of Leeds Leeds UK

This paper presents a novel WLAN-based system configuration employing Coded Multi-Carrier Code-Division- Multiplexing technology (CMC-CDM), as a potentially superior alternative to the currently standardized Coded OFDM (COFDM) technology. To further improve the performance of the system and reduce its complexity, a new concept of Chase detection is applied at the receiver. A comprehensive investigation has shown that under the appropriate conditions, the proposed system is able to show considerable advantage over COFDM. We believe that this work will contribute to the motivation of deploying CMC-CDM as an alternative approach for Next Generation of wireless systems.

关键词： detection algorithms OFDM Multiaccess communication Multicarrier code division multiple access Detectors Fading Robustness WiMAX Time division multiple access Multiple access interference

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Distributed detection over adaptive networks based on diffusion estimation schemes

Distributed detection over adaptive networks based on diffus...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Federico S. Cattivelli Ali H. Sayed Department of Electrical Engineering University of California Los Angeles CA USA

We study the problem of distributed detection, where a set of nodes are required to decide between two hypotheses based on their measurements. We seek fully distributed implementations, where all nodes make individual decisions by communicating with their immediate neighbors, and no fusion center is necessary. This scheme provides the network with more flexibility, saves energy for communication and networking resources. Our distributed detection algorithm is based on a previously proposed distributed estimation algorithm. We establish the connection between the detection and estimation problems, propose a distributed detection algorithm, and analyze the performance of the algorithm in terms of its probabilities of detection and false alarm. We also provide simulation results comparing with other cooperation schemes.

关键词： Adaptive systems detection algorithms Time measurement Iterative algorithms Performance analysis Resonance light scattering Electric variables measurement Algorithm design and analysis Context Adaptive filters

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Moving Object detection and Tracking Based on WADM

Moving Object Detection and Tracking Based on WADM

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IEEE International Symposium on Computer Network and Multimedia Technology, CNMT

作者： Feng-yan Zuo Sheng-fa Gao Shandong Library Jinan Shandong China College of Computer Science and Technology Shandong University Jinan Shandong China

In order to solve the problem of slowly moving object detection and tracking, this paper proposes a new weighted accumulative difference method and works out a weights setting algorithm to fast detect the slowly moving object. We obtain the interest points from the moving area detected, then fix the matching range with the maximum velocity principle and work out a non-retrospective mismatch detection algorithm with the consistency principle. These methods upwards can enhance the efficiency and precision of our tracking system.

关键词： Object detection Image sequences Image motion analysis Background noise Libraries Educational institutions Computer science detection algorithms Aerospace control Automatic control

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Advanced hyperspectral detection based on elliptically contoured distribution models and operator feedback

Advanced hyperspectral detection based on elliptically conto...

引用

Applied Imagery Pattern Recognition Workshop (AIPR)

作者： A. Schaum Naval Research Laboratory Inc. Washington D.C. DC USA

In autonomous hyperspectral remote sensing systems, the physical causes of false alarms are not all understood. Some arise from vagaries in sensor performance, especially in non-visible wavelengths. Consequently, many false target declarations are characterized simply as outliers, anomalies conforming to no physical or statistical models. Other false alarms arise from clutter spectra too similar to target spectra. To eliminate the recurrence of such difficult errors, deployed systems should allow operator feedback to their signal processing systems. Here we describe how a hyperspectral system using even advanced detection algorithms, based on a elliptically contoured distribution models, can be enhanced by allowing it to learn from its mistakes.

关键词： Feedback Hyperspectral imaging Hyperspectral sensors detection algorithms Signal processing algorithms Equations Covariance matrix Matched filters Laboratories Testing

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Local-global background modeling for anomaly detection in hyperspectral images

Local-global background modeling for anomaly detection in hy...

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Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Eyal Madar Oleg Kuybeda David Malah Meir Barzohar Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel

In this paper, we address the problem of unsupervised detection of anomalies in hyperspectral images. Our proposed method is based on a novel statistical background modeling approach that combines local and global approaches. The local-global background model has the ability to adapt to all nuances of the background process like local approaches but avoids over-fitting due to a too high number of degrees of freedom, which produces a high false alarm rate. This is done by constraining the local background models to be interrelated. The results strongly prove the effectiveness of the proposed algorithm. We experimentally show that our local-global algorithm performs better than several other global or local anomaly detection techniques, such as the well known RX or its Gaussian Mixture version (GMRX).

关键词： Hyperspectral imaging detection algorithms Hyperspectral sensors Remote sensing Training data Design methodology Detectors Greedy algorithms Vegetation mapping Soil

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