Reidentification of Persons Using Clothing Features in Real-Life Video by Guodong Zhang, Peilin Jiang, Kazuyuki Matsumoto, Minoru Yoshida, Kenji Kita

“…Finally, we used the Gaussian mixture model (GMM) to show features for person reidentification, because the main color feature of GMM is more adaptable for scene changes, and improve the stability of the retrieved results for different color spaces in various scenes. …”
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A Robust Approach for Speaker Identification Using Dialect Information by Shahid Munir Shah, Muhammad Moinuddin, Rizwan Ahmed Khan

“…For automated dialect identification, the spectral and prosodic features have been used in conjunction with Gaussian mixture model (GMM). In the second step, the speaker is identified using a multilayer perceptron (MLP)-based speaker identification system, which gets aggregated input from the first step, i.e., dialect identification along with prosodic and spectral features. …”
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A problem-agnostic approach to feature selection and analysis using SHAP by John T. Hancock, Taghi M. Khoshgoftaar, Qianxin Liang

“…When data of one class is available, a one-class classifier, such as Gaussian Mixture Model (GMM) can be used in combination with SHAP for determining feature importance, and for feature selection. …”
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A Unified Bayesian Model for Generalized Community Detection in Attribute Networks by Qiang Tian, Wenjun Wang, Yingjie Xie, Huaming Wu, Pengfei Jiao, Lin Pan

“…The proposed model is composed of two closely correlated parts by a transition matrix; we first apply the concept of a mixture model to describe network regularities and then adjust the classic Latent Dirichlet Allocation (LDA) topic model to identify community semantically. …”
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Short-Term Traffic Prediction considering Spatial-Temporal Characteristics of Freeway Flow by Jiaqi Wang, Yingying Ma, Xianling Yang, Teng Li, Haoxi Wei

“…First, the Gaussian mixture model (GMM) based on Kullback–Leibler divergence and Grey relation analysis coefficient calculated by the data in the corresponding period is proposed. …”
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Scale-Dependent Signal Identification in Low-Dimensional Subspace: Motor Imagery Task Classification by Qingshan She, Haitao Gan, Yuliang Ma, Zhizeng Luo, Tom Potter, Yingchun Zhang

“…Our method trains a Gaussian mixture model (GMM) of the composite data, which is comprised of the IMFs from both the original signal and noise, by employing kernel spectral regression to reduce the dimension of the composite data. …”
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Detection and Adaptive Video Processing of Hyperopia Scene in Sports Video by Qingjie Chen, Minkai Dong

“…When using Gaussian mixture model for modeling, improve the parts with differences, and keep the unmatched Gaussian distribution so that the modeling effect is similar to the actual background; the binary image is obtained through the difference between frames and the threshold, and the motion change domain is extracted through mathematical morphological filtering, and finally, the moving target is detected. …”
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Hierarchical Task-Parameterized Learning from Demonstration for Collaborative Object Movement by Siyao Hu, Katherine J. Kuchenbecker

“…Our approach uses the task-parameterized Gaussian mixture model (TP-GMM) algorithm to encode sets of demonstrations in separate models that each correspond to a different task situation. …”
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Analysis of Joint Angular Distribution for Nonreciprocal Beams via the Mixture of Gaussian Distribution Based on Ray-Tracing by Jiachi Zhang, Liu Liu, Zhenhui Tan, Kai Wang, Tao Zhou

“…Furthermore, to characterize the relationship between quasiangles of departure (AoD) and quasiangles of arrival (AoA), the Gaussian mixture model (GMM) is adopted and the expectation-maximization (EM) algorithm is used to estimate the unknown parameters of GMM. …”
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Migration Law and Influence of Proppant in Segmented Multicluster Fracturing Wellbore of Deep Shale Horizontal Well by Tingxue Jiang, Haitao Wang, Juanming Wei, Guanyu Zhong, Yucheng Zhao, Yushi Zou

“…In order to deeply analyze the influence mechanism and law of proppant flow in the wellbore on multiple fractures and propagation, Firstly, based on the theoretical knowledge of computational fluid dynamics (CFD), a numerical model of solid-liquid two-phase flow of proppant migration in horizontal wellbore is established, which is calculated and solved by using the Euler-Euler multiphase-flow mixture model, and the effects of different influencing factors on the migration and distribution of proppant in wellbore are studied. …”
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K-Means Cluster for Seismicity Partitioning and Geological Structure Interpretation, with Application to the Yongshaba Mine (China) by Xueyi Shang, Xibing Li, A. Morales-Esteban, Longjun Dong, Kang Peng

“…In this paper, seismic event location (X,Y,Z) and Euclidean distance were selected as the K-Means cluster, the Gaussian mixture model (GMM), and the self-organizing maps (SOM) input features and cluster determination measurement, respectively, and 1516 seismic events (M>-1.5) obtained from the Yongshaba mine (China) were chosen for the cluster analysis. …”
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Speed Distribution Prediction of Freight Vehicles on Mountainous Freeway Using Deep Learning Methods by Yuren Chen, Yu Chen, Bo Yu

“…Driving speed was characterized by the bimodal Gauss mixture model. RNN and its variants including long short-term memory (LSTM) and RNN and gated recurrent units (GRUs) were utilized to predict speed distribution in a spatial-temporal dimension with KL divergence being the loss function. …”
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Dynamics of SARS-CoV-2 infection over two epidemic waves in Manaus, Brazil: A serological study of seven thousand blood donors. by Neal Alexander, Christopher Dye, Michael P Busch, Lewis Buss, Carlos A Prete, Oliver J Brady, Paul Mee, Claudia M M Abrahim, Myuki A E Crispim, Allyson G da Costa, Tassila Salomon, Philippe Mayaud, Márcio K Oikawa, Nuno R Faria, Ester C Sabino

“…Seroconversion was inferred by a mixture model for serial values from the Abbott Architect SARS-CoV-2 nucleocapsid (N) IgG assay. …”
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Traffic Risk Assessment Based on Warning Data by Tao Wang, Binbin Chen, Yuzhi Chen, Shejun Deng, Jun Chen

“…The risk classification thresholds were determined based on the Gaussian Mixture Model algorithm. Finally, a spatial econometric model was used to quantify the impact of built environment factors characterized by Point of Interest (POI) data on regional traffic risk, with the results of risk class classification as the dependent variable. …”
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Characterizing Sparse Spectral Diversity Within a Homogenous Background: Hydrocarbon Production Infrastructure in Arctic Tundra near Prudhoe Bay, Alaska by Daniel Sousa, Latha Baskaran, Kimberley Miner, Elizabeth Josephine Bushnell

“…Analysis involves two stages: first, computing the mixture residual of a generalized linear spectral mixture model; and second, nonlinear dimensionality reduction via manifold learning. …”
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Articulatory-to-Acoustic Conversion Using BiLSTM-CNN Word-Attention-Based Method by Guofeng Ren, Guicheng Shao, Jianmei Fu

“…Finally, Root Mean Square Error (RMSE), Mean Mel-Cepstral Distortion (MMCD), and correlation coefficient have been used to evaluate the conversion effect and for comparison with Gaussian Mixture Model (GMM) and BiLSTM of recurrent neural network (BiLSTM-RNN). …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Evaluated the performance of a system by using the following classifiers as Non-Linear Regression—NLR, Linear Regression—LR, Gaussian Mixture Model—GMM, Expectation Maximization—EM, Bayesian Linear Discriminant Analysis—BLDA, Softmax Discriminant Classifier—SDC, and Support Vector Machine with Radial Basis Function kernel—SVM-RBF classifier on two publicly available datasets namely the Nordic Islet Transplant Program (NITP) and the PIMA Indian Diabetes Dataset (PIDD). …”
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Incremental Instance-Oriented 3D Semantic Mapping via RGB-D Cameras for Unknown Indoor Scene by Wei Li, Junhua Gu, Benwen Chen, Jungong Han

“…To obtain accurate point cloud cluster, we adopt the Gaussian mixture model as an optimizer after processing 2D to 3D projection. …”
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Origin-Destination-Based Travel Time Reliability under Different Rainfall Intensities: An Investigation Using Open-Source Data by Qi Zhang, Hong Chen, Hongchao Liu, Wei Li, Yibin Zhang

“…The authors classified three years of travel time data in downtown Boston into one hundred origin-destination pairs and integrated them with the weather data (rain). A lognormal mixture model was applied to fit travel time distributions and calculate the buffer index. …”
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Sleep behaviour and cardiorespiratory fitness in patients after percutaneous coronary intervention during cardiac rehabilitation: protocol for a longitudinal study by Jie Zhou, Jing Wu, Lan Huang, Yiyan Wang, Husheng Li, Xubo Wu

“…This information will be collected four times within 6 months of CR, and patients will be followed up for 1 year. The growth mixture model will be used to analyse the longitudinal sleep data. …”
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