Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation by Hossein Rabbani, Rahele Kafieh, Mahdi Kazemian Jahromi, Sahar Jorjandi, Alireza Mehri Dehnavi, Fedra Hajizadeh, Alireza Peyman

“…In this paper, segmentation methods such as Gaussian Mixture Model (GMM), Graph Cut, and Level Set are used for automatic segmentation of three clinically important corneal layer boundaries on OCT images. …”
Get full text

Determination of the area index of lettuce leaves with a monocular camera by Laimonas Kairiūkštis, Başak Yalçıner, Emre Özkul

“…The integration of Gaussian Mixture Model clustering with the dataset further enhanced the precision of the lettuce growth and harvest predictions.…”
Get full text

Transforming traffic accident investigations: a virtual-real-fusion framework for intelligent 3D traffic accident reconstruction by Yanzhan Chen, Qian Zhang, Fan Yu

“…Finally, the Gaussian Mixture Model assisted by MIPBO accurately separates various traffic elements in the accident scenes, demonstrating higher effectiveness compared to other classical clustering algorithms.…”
Get full text

Study on the Effect of Surface Roughness on the Spectral Unmixing of Mixed Pixels by Haonan Zhang, Xingping Wen, Junlong Xu, Dayou Luo, Ping He

“…The linear spectral mixture model is used for spectral decomposition, and the effect of roughness on the unmixing precision of mixed pixels was studied. …”
Get full text

RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks by Shengren Hou, Shuyi Gao, Weijie Xia, Edgar Mauricio Salazar Duque, Peter Palensky, Pedro P. Vergara

“…A standout feature of RL-ADN is its data augmentation module, based on Gaussian Mixture Model and Copula (GMC) functions, which elevates the performance ceiling of DRL agents, achieving an average performance improvement of 21.43%, 1.08%, 2.76%, by augmenting five-year, one-year and three-month data, respectively. …”
Get full text

Few-shot Remote Sensing Imagery Recognition with Compositionality Inductive Bias in Hierarchical Representation Space by Shichao Zhou, Zhuowei Wang, Zekai Zhang, Wenzheng Wang, Yingrui Zhao, Yunpu Zhang

“…We establish a clustering-oriented factorized representation with a mixture model to represent multipart distributions of tokens. …”
Get full text

Toxicity evaluation of herbicides used in sugarcane crops to Zebrafish (Danio rerio) by Gabrielli Aparecida Sanches Tesolin, Marina Menezes Marson, Claudio Martín Jonsson, António José Arsénia Nogueira, Daniel Andrade de Siqueira Franco, Sydnei Dionísio Batista de Almeida, Marcus Barifouse Matallo, Monica Accaui Marcondes de Moura

“…LC50-96h was determined to 41.705 ± 8.373 mg/L to Gesapax 500 and 55.460 ± 20.826 mg/L to Velpar K. The mixture model that best describes the relationship between the two components is independent action and toxicity of the mixture is dose-dependent, occurring antagonism at low doses and synergism at high doses. …”
Get full text

Fishy Business—Assessing the Efficacy of Active and Passive eDNA to Describe the Fish Assemblage of a River in Southwestern Western Australia to Support Effective Monitoring by Emma R. Stevens, Josephine Hyde, Leah S. Beesley, Daniel C. Gwinn, Suzanne Thompson, Lenore Morris, Paige R. Wilson, Deirdre B. Gleeson

“…Here, we utilize a hierarchical multispecies N‐mixture model to compare three fish sampling methods: traditional fyke netting and active and passive environmental DNA sampling along a 30 km stretch of the Canning River in Western Australia. …”
Get full text

A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission by Benjamin Sobkowiak, Patrick Cudahy, Melanie H. Chitwood, Taane G. Clark, Caroline Colijn, Louis Grandjean, Katharine S. Walter, Valeriu Crudu, Ted Cohen

“…Methods We employed a Gaussian mixture model to cluster allele frequencies at mixed sites (hSNPs) in each sample to identify signals of multiple strains. …”
Get full text

Segmentation of Dynamic Total-Body [18F]-FDG PET Images Using Unsupervised Clustering by Maria K. Jaakkola, Maria Rantala, Anna Jalo, Teemu Saari, Jaakko Hentilä, Jatta S. Helin, Tuuli A. Nissinen, Olli Eskola, Johan Rajander, Kirsi A. Virtanen, Jarna C. Hannukainen, Francisco López-Picón, Riku Klén

“…These criteria filtered out most of the commonly used approaches, leaving only two clustering methods, k-means and Gaussian mixture model (GMM), for further analyses. We combined k-means with two different preprocessing approaches, namely, principal component analysis (PCA) and independent component analysis (ICA). …”
Get full text

Comparison of various clustering algorithms efficiency by Tomas Ruzgas

“… This article illustrates the problem of clustering efficiency of Gaussian mixture models using various clustering methods. The results of investigation by simulation are discussed. …”
Get full text

Longitudinal Associations Between Sleep Disturbance Trajectories and Internet Gaming Disorder Mediated by Self-Control: A Six-Wave Longitudinal Investigation by Liu H, Qiao X, Shi X

“…Sleep disturbance was measured from Time 1 to Time 4, self-control was measured at Time 5, and Internet gaming disorder was measured at Time 6. Growth mixture modeling (GMM) was applied to identify latent classes of sleep disturbance over the four waves. …”
Get full text

Analysis of a Pareto Mixture Distribution for Maritime Surveillance Radar by Graham V. Weinberg, Daniel Finch

“…Given the success of mixture distributions in radar, it is thus of interest to consider the effect of Pareto mixture models. This paper introduces a formulation of a Pareto intensity mixture distribution and investigates coherent multilook radar detector performance using this new clutter model. …”
Get full text

Protocol for identifying Mycobacterium tuberculosis infection status through airway microbiome profiling by Geoffrey Olweny, Moses Levi Ntayi, Edward Kyalo, Alex Kayongo

“…We outline procedures for processing microbiome data, calculating diversity measures, and fitting Dirichlet multinomial mixture models. Additionally, we provide steps for analyzing taxonomic relative and differential abundances, as well as identifying potential biomarkers associated with infection status.For complete details on the use and execution of this protocol, please refer to Kayongo et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.…”
Get full text

Human-interpretable clustering of short text using large language models by Justin K. Miller, Tristram J. Alexander

“…In this study, clusters are found in the embedding space using Gaussian mixture modelling. The resulting clusters are found to be more distinctive and more human-interpretable than clusters produced using the popular methods of doc2vec and latent Dirichlet allocation. …”
Get full text

EMIKNet: Expanding Multiple-Instance Inverse Kinematics Network for Multiple End-Effector and Multiple Solutions by Youn-Jae Go, Jun Moon

“…The proposed method is constructed via interconnected Gaussian Mixture Models (GMM), which consist of two main components: (i) a hierarchical computation framework for calculating joint angles while considering joint limits, and (ii) a ‘sub-link’ concept to reduce the hierarchical computation. …”
Get full text

Unsupervised machine and deep learning methods for structural damage detection: A comparative study by Zilong Wang, Young‐Jin Cha

“…., K‐nearest neighbors method, Gaussian mixture models, one‐class support vector machines, density peaks‐based fast clustering method) and one deep learning method using a deep auto‐encoder are selected. …”
Get full text

Patterns of Change in Cognitive Function over Six Months in Adults with Chronic Heart Failure by Barbara Riegel, Christopher S. Lee, Dale Glaser, Stephen T. Moelter

“…A battery of neuropsychological tests was administered to 279 adults with chronic systolic or diastolic HF at baseline, three and six months. Growth mixture modeling (GMM) was used to model the measure anticipated to be most sensitive, the digit symbol substitution task (DSST). …”
Get full text

Behaviour as an indicator of cyclic trends in abundance of Canada lynx (Lynx canadensis) and snowshoe hare (Lepus americanus) by Shannon M. Crowley, Chris J. Johnson, Dexter P. Hodder

“…Our first objective was to determine if N-mixture models, camera occurrence rates, and behaviours could be used to monitor trends in cyclic abundance. …”
Get full text

Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification by Yajie Zou, Xinzhi Zhong, John Ash, Ziqiang Zeng, Yinhai Wang, Yanxi Hao, Yichuan Peng

“…To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering) to select “similar” sites for building SPFs are developed. …”
Get full text