Results 171 to 180 of about 7,207 (210)
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Bearing Fault Diagnosis Using Gaussian Mixture Models (GMMs)
Applied Mechanics and Materials, 2007This paper presents a novel method for bearing fault diagnosis based on wavelet transform and Gaussian mixture models (GMMs). Vibration signals for normal bearings, bearings with inner race faults, outer race faults and ball faults were acquired from a motor-driven experimental system. The wavelet transform was used to process the vibration signals and
J. Sun, Gang Yu, Chang Ning Li
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Speaker Verification Using Gaussian Mixture Model (GMM)
2011This paper applies GMM for SV on Malay speech. The speaker models were trained on maximum likelihood estimated. The system was evaluated with 23 client speakers with 56 imposters. Malay clean speech data was used. 20 training of 3.5s utterances are used. The best performance achieved using 256-Gaussian imposter model and 32-Gaussian client model gave 3.
Shaikh Salleh, Sheikh Hussain +5 more
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Unsupervised Learning of Finite Gaussian Mixture Models (GMMs): A Greedy Approach
2011In this work we propose a clustering algorithm that learns on-line a finite gaussian mixture model from multivariate data based on the expectation maximization approach. The convergence of the right number of components as well as their means and covariances is achieved without requiring any careful initialization.
Nicola Greggio +2 more
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Gaussian Mixture Model (GMM) Based Dynamic Object Detection and Tracking
2019 International Conference on Unmanned Aircraft Systems (ICUAS), 2019In this paper, we have addressed the problem of real-time detection and tracking of dynamic objects using quadrotors. We have developed a novel object detection algorithm by analyzing and matching the color and spacial features of the target from monocular image sequences.
Vishnu Anand +3 more
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Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
Test utterance parameterization (TUP) using Gaussian mixture models (GMMs) has recently been shown to be beneficial for speaker indexing due to its computational efficiency and identical accuracy compared to classic GMM-based recognizers. We show that TUP can also lead to more accurate speaker recognition.
Hagai Aronowitz +2 more
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Test utterance parameterization (TUP) using Gaussian mixture models (GMMs) has recently been shown to be beneficial for speaker indexing due to its computational efficiency and identical accuracy compared to classic GMM-based recognizers. We show that TUP can also lead to more accurate speaker recognition.
Hagai Aronowitz +2 more
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New image reconstruction algorithm for CCERT: LBP + Gaussian mixture model (GMM) clustering
Measurement Science and Technology, 2020Abstract This work focuses on the study of the image reconstruction algorithm of capacitively coupled electrical resistance tomography (CCERT). With the combination of a linear back projection (LBP) algorithm and an unsupervised Gaussian mixture model (GMM) algorithm, a new image reconstruction algorithm for CCERT is proposed. The LBP
Yuxin Wang +5 more
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International Journal of Pattern Recognition and Artificial Intelligence, 2014
For solving speaker identification problems, the approach proposed by Reynolds [IEEE Signal Process. Lett.2 (1995) 46–48], using Gaussian Mixture Models (GMMs) based on Mel Frequency Cepstral Coefficients (MFCCs) as features, is one of the most effective available in the literature.
Amita Pal +3 more
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For solving speaker identification problems, the approach proposed by Reynolds [IEEE Signal Process. Lett.2 (1995) 46–48], using Gaussian Mixture Models (GMMs) based on Mel Frequency Cepstral Coefficients (MFCCs) as features, is one of the most effective available in the literature.
Amita Pal +3 more
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Gaussian Mixture Model (GMM) Based Object Detection and Tracking using Dynamic Patch Estimation
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019In this paper, we have developed a Gaussian Mixture Model (GMM) based algorithm with dynamic patch estimation for real-time detection and tracking of a known object. This research work detects the object of interest, estimates its 3-D position using Extended Kalman Filter (EKF) and generates the control output to the quad-rotor to track the target. The
Vishnu Anand +3 more
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An Adaptive Segmentation Method Based on Gaussian Mixture Model (GMM) Clustering for DNA Microarray
2014 International Conference on Intelligent Computing Applications, 2014Microarray allows us to efficiently analyse valuable gene expression data. In this paper we propose a effective methodology for analysis of microarrays. Earlier a new gridding algorithm is proposed to address all individual spots and to determine their borders.
M. Parthasarathy, R. Ramya, A. Vijaya
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2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
In this paper a Gaussian mixture model (GMM) classifier, called GMM identifier, is proposed as an efficient post-processing method to enhance the performance of a CMM-based speaker verification system; such as Gaussian mixture model universal background model (GMM-UBM) and structural Gaussian mixture models with structural background model (SGMM-SBM ...
Rahim Saeidi +2 more
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In this paper a Gaussian mixture model (GMM) classifier, called GMM identifier, is proposed as an efficient post-processing method to enhance the performance of a CMM-based speaker verification system; such as Gaussian mixture model universal background model (GMM-UBM) and structural Gaussian mixture models with structural background model (SGMM-SBM ...
Rahim Saeidi +2 more
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