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Artykuły w czasopismach na temat "GMM based scheme"

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Ding, Ing Jr, Chih Ta Yen, and Che Wei Chang. "Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis." Applied Mechanics and Materials 479-480 (December 2013): 1006–9. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.1006.

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In this paper, a fusion scheme that combines Gaussian mixture model (GMM) calculations and formant feature analysis, called GMM-Formant, is proposed for classification of Chinese popular songs. Generally, automatic classification of popular music could be performed by two main categories of techniques, model-based and feature-based approaches. In model-based classification techniques, GMM is widely used for its simplicity. In feature-based music recognition, the formant parameter is an important acoustic feature for evaluation. The proposed GMM-Formant method takes use of linear interpolation
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Alharbi, Bayan, and Hanan S. Alshanbari. "Face-voice based multimodal biometric authentication system via FaceNet and GMM." PeerJ Computer Science 9 (July 11, 2023): e1468. http://dx.doi.org/10.7717/peerj-cs.1468.

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Information security has become an inseparable aspect of the field of information technology as a result of advancements in the industry. Authentication is crucial when it comes to dealing with security. A user must be identified using biometrics based on certain physiological and behavioral markers. To validate or establish the identification of an individual requesting their services, a variety of systems require trustworthy personal recognition schemes. The goal of such systems is to ensure that the offered services are only accessible by authorized users and not by others. This case study
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Gupta, Monika, Smriti Srivastava, Gopal Chaudhary, Manju Khari, and Javier Parra Fuente. "Voltage Regulation using Probabilistic and Fuzzy Controlled Dynamic Voltage Restorer for Oil and Gas Industry." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, Supp02 (2020): 49–64. http://dx.doi.org/10.1142/s0218488520400139.

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In a power distribution system, faults occurring can cause voltage sag that can affect critical loads connected in the power network which can cause serious effects in the oil and gas industry. The objective of this paper is to design and implement an efficient and economical dynamic voltage restorer (DVR) to compensate for voltage sag conditions in the oil and gas industry. Due to the complexity and sensitivity of loads, a short voltage sag duration can still cause severe power quality problems to the entire system. Dynamic Voltage Restorer (DVR) is a static series compensating type custom po
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Mamyrbayev, O., A. Akhmediyarova, A. Kydyrbekova, N. O. Mekebayev, and B. Zhumazhanov. "BIOMETRIC HUMAN AUTHENTICATION SYSTEM THROUGH SPEECH USING DEEP NEURAL NETWORKS (DNN)." BULLETIN 5, no. 387 (2020): 6–15. http://dx.doi.org/10.32014/2020.2518-1467.137.

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Biometrics offers more security and convenience than traditional methods of identification. Recently, DNN has become a means of a more reliable and efficient authentication scheme. In this work, we compare two modern teaching methods: these two methods are methods based on the Gaussian mixture model (GMM) (denoted by the GMM i-vector) and methods based on deep neural networks (DNN) (denoted as the i-vector DNN). The results show that the DNN system with an i-vector is superior to the GMM system with an i-vector for various durations (from full length to 5s). DNNs have proven to be the most eff
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Chaddad, Ahmad. "Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models." International Journal of Biomedical Imaging 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/868031.

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This paper presents a novel method for Glioblastoma (GBM) feature extraction based on Gaussian mixture model (GMM) features using MRI. We addressed the task of the new features to identify GBM using T1 and T2 weighted images (T1-WI, T2-WI) and Fluid-Attenuated Inversion Recovery (FLAIR) MR images. A pathologic area was detected using multithresholding segmentation with morphological operations of MR images. Multiclassifier techniques were considered to evaluate the performance of the feature based scheme in terms of its capability to discriminate GBM and normal tissue. GMM features demonstrate
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Chen, Rong, Yuzhu Bai, Yong Zhao, Zhijun Chen, and Tao Sheng. "Safe Proximity Operation to Rotating Non-Cooperative Spacecraft with Complex Shape Using Gaussian Mixture Model-Based Fixed-Time Control." Applied Sciences 10, no. 17 (2020): 5986. http://dx.doi.org/10.3390/app10175986.

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This paper studies the safety control problem for rotating spacecraft proximity maneuver in presence of complex shaped obstacles. First, considering the attitude change of the target spacecraft, a dynamic model of close-range relative motion in a body-fixed coordinate system is derived using a novel approach. Then, the Gaussian mixture model (GMM) is utilized to reconstruct the complex shape of the spacecraft, and a novel GMM-based artificial potential function (APF) is proposed to represent the collision avoidance requirement. By combining GMM-based APF with fixed-time stability methodology,
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Zergat, Kawthar Yasmine, and Abderrahmane Amrouche. "New scheme based on GMM-PCA-SVM modelling for automatic speaker recognition." International Journal of Speech Technology 17, no. 4 (2014): 373–81. http://dx.doi.org/10.1007/s10772-014-9235-7.

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Chen, Guang Hua, and Gui Zhi Sheng. "Detection of Moving Objects Based on Mixture Gaussian Model." Advanced Materials Research 1039 (October 2014): 274–79. http://dx.doi.org/10.4028/www.scientific.net/amr.1039.274.

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The paper proposes an improved adaptive Gaussian mixture model (GMM) approach with online EM algorithms for updating, which solves the video segmentation problems carried by busy environment and illumination change. Different learning rates are set for foreground district and background district respectively, which improves the convergence speed of background model. A shadow removal scheme is also introduced for extracting complete moving objects. It is based on brightness distortion and chromaticity distortion in RGB color space. Morphological filtering and connected components analysis algor
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KIM, Y., S. JEONG, and D. KIM. "A GMM-Based Target Classification Scheme for a Node in Wireless Sensor Networks." IEICE Transactions on Communications E91-B, no. 11 (2008): 3544–51. http://dx.doi.org/10.1093/ietcom/e91-b.11.3544.

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Chen, Joy Iong-Zong, and P. Hengjinda. "Based on machine learning scheme to develop a smart robot embedded with GMM-UBM." Journal of Intelligent & Fuzzy Systems 40, no. 4 (2021): 7925–37. http://dx.doi.org/10.3233/jifs-189615.

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Smart Robot embedded with GMM-UBM (Gaussian mixture model- universal background model) based on the machine learning scheme is presented in the article. Authors have designed a smart robot for the farmer and which is designed controlled by the concept of machine learning. On the other hand, the techniques of machine learning are applied to develop a smart robot for helping farmers recognize the environment conditions, e.g. weather, and disease protection in rice or plant. The smart robot is implemented to detect and to recognize the environment conditions around a fixed area. The sensing way t
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