Results 11 to 20 of about 33,807 (240)
Using Deep-Learning for 5G End-to-End Delay Estimation Based on Gaussian Mixture Models
Information, 2023 Deep learning is used in various applications due to its advantages over traditional Machine Learning (ML) approaches in tasks encompassing complex pattern learning, automatic feature extraction, scalability, adaptability, and performance in general ...
Diyar Fadhil, Rodolfo Oliveira
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Improved Bearings-Only Multi-Target Tracking with GM-PHD Filtering
Sensors, 2016 In this paper, an improved nonlinear Gaussian mixture probability hypothesis density (GM-PHD) filter is proposed to address bearings-only measurements in multi-target tracking.
Qian Zhang, Taek Lyul Song
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Meikuang Anquan, 2020 An online detection method for longitudinal tear of mine conveyor belt is proposed, and the method combines infrared image features with improved Gaussian Mixture Model(GMM). An adaptive hybrid median filtering technique is designed.
GUO Jian, QIAO Tiezhu, CHE Jian
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Porting concepts from DNNs back to GMMs [PDF]
, 2013 Deep neural networks (DNNs) have been shown to outperform Gaussian Mixture Models (GMM) on a variety of speech recognition benchmarks. In this paper we analyze the differences between the DNN and GMM modeling techniques and port the best ideas from the ...
Demuynck, Kris, Triefenbach, Fabian
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S-TRANSFORM AND GAUSSIAN MIXTURE MODEL FOR ACOUSTIC SCENE CLASSIFICATION
International Journal of Advances in Signal and Image Sciences, 2020 In this study, Acoustic Scene Classification (ASC) system is designed with the help of S-transform and Gaussian Mixture Model (GMM). The S-transform is an extension of continuous wavelet transform that combines the progressive resolution with phase ...
Santosh Kumar Srivastava
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Clustering compositional data using Dirichlet mixture model.
PLoS ONE, 2022 A model-based clustering method for compositional data is explored in this article. Most methods for compositional data analysis require some kind of transformation. The proposed method builds a mixture model using Dirichlet distribution which works with
Samyajoy Pal, Christian Heumann
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Automatic Speaker Recognition with Multi-Resolution Gaussian Mixture Models (MR-GMM) [PDF]
The International Journal of Forensic Computer Science, 2009 Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution).
D’Almeida, Frederico Quadros +3 more
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Multi-stream gaussian mixture model based facial feature localization=Çoklu gauss karışım modeli tabanlı yüz öznitelikleri bulma algoritması [PDF]
, 2008 This paper presents a new facial feature localization system which estimates positions of eyes, nose and mouth corners simultaneously. In contrast to conventional systems, we use the multi-stream Gaussian mixture model (GMM) framework in order to ...
Ekenel, Hazım K. +4 more
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Kernel Analysis Based on Dirichlet Processes Mixture Models
Entropy, 2019 Kernels play a crucial role in Gaussian process regression. Analyzing kernels from their spectral domain has attracted extensive attention in recent years. Gaussian mixture models (GMM) are used to model the spectrum of kernels.
Jinkai Tian, Peifeng Yan, Da Huang
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The learning method of robot teaching sewing motion
Xi'an Gongcheng Daxue xuebao, 2022 In order to realize the robot′s learning of teaching sewing motion, a robot motion learning method based on Gaussian Mixture Model (GMM) -Gaussian Mixture Regression (GMR) was proposed.
WANG Haoyi, WANG Xiaohua, WANG Wenjie
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