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   Articles with "unsupervised clustering" as a keyword



Autoencoder-based unsupervised clustering and hashing

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recommendations! Published in 2020 at "Applied Intelligence"

DOI: 10.1007/s10489-020-01797-y

Abstract: Faced with a large amount of data and high-dimensional data information in a database, the existing exact nearest neighbor retrieval methods cannot obtain ideal retrieval results within an acceptable retrieval time. Therefore, researchers have begun… read more here.

Keywords: autoencoder based; based unsupervised; clustering hashing; unsupervised clustering ... See more keywords

Fiber-distance-based unsupervised clustering of MR tractography data

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recommendations! Published in 2019 at "Journal of Neuroscience Methods"

DOI: 10.1016/j.jneumeth.2019.108361

Abstract: BACKGROUND MR tractography from diffusion tensor imaging provides a non-invasive way to explore white matter pathways in the human brain. However, a challenge to extracting reliable anatomical information from these data is the use of… read more here.

Keywords: tractography; fiber distance; unsupervised clustering; dbscan based ... See more keywords

Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space

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recommendations! Published in 2022 at "Journal of chemical theory and computation"

DOI: 10.1021/acs.jctc.2c00396

Abstract: We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This work determines clusters via the Gaussian mixture model (GMM) in an entirely automatic manner… read more here.

Keywords: gmm; unsupervised clustering; training; orbital based ... See more keywords

Promoting convergence and efficacy of open‐domain question answering via unsupervised clustering

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recommendations! Published in 2024 at "Electronics Letters"

DOI: 10.1049/ell2.13239

Abstract: Open‐Domain Question Answering (ODQA) has attracted increasing interests due to its extensive applications in search engines and smart robots. In the experiments, it is observed that the convergence of the method has a huge effect… read more here.

Keywords: open domain; convergence efficacy; unsupervised clustering; domain question ... See more keywords

Unsupervised clustering to differentiate rheumatoid arthritis patients based on proteomic signatures.

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recommendations! Published in 2023 at "Scandinavian journal of rheumatology"

DOI: 10.1080/03009742.2023.2196781

Abstract: OBJECTIVE Patients with rheumatoid arthritis (RA) have different presentations and prognoses. Cluster analysis based on proteomic signatures creates independent phenogroups of patients with different pathophysiological backgrounds. We aimed to identify distinct pathophysiological clusters of RA… read more here.

Keywords: proteomic signatures; unsupervised clustering; patients based; rheumatoid arthritis ... See more keywords

Multi-omics integration - a comparison of unsupervised clustering methodologies

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recommendations! Published in 2019 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbx167

Abstract: With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work,… read more here.

Keywords: multi omics; comparison unsupervised; integration; unsupervised clustering ... See more keywords

Unsupervised clustering of catalog-driven features for characterizing temporal evolution of labquake stress

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recommendations! Published in 2024 at "Geophysical Journal International"

DOI: 10.1093/gji/ggae071

Abstract: Earthquake forecasting poses significant challenges, especially due to the elusive nature of stress states in fault systems. To tackle this problem, we employ features derived from seismic catalogs obtained from acoustic emission (AE) signals recorded… read more here.

Keywords: temporal evolution; stress; catalog driven; unsupervised clustering ... See more keywords

Safe Semi-Supervised Fuzzy ${C}$ -Means Clustering

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2929307

Abstract: With the rapid increase in the number of collected data samples, semi-supervised clustering (SSC) has become a useful mining tool to find an intrinsic data structure with the help of prior knowledge. The common used… read more here.

Keywords: safe semi; unsupervised clustering; semi supervised; prior knowledge ... See more keywords

Infrared Thermography-Based Insulator Fault Classification via Unsupervised Clustering and Semi-Supervised Learning

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3404930

Abstract: Power substations play a crucial role in ensuring the reliable transmission of electricity to residential and commercial establishments. This paper addresses the critical issue of insulator fault detection in electric substations, emphasizing the importance of… read more here.

Keywords: supervised learning; infrared thermography; insulator fault; insulator ... See more keywords

Unsupervised Clustering of Seismic Signals Using Deep Convolutional Autoencoders

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recommendations! Published in 2019 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2019.2909218

Abstract: In this letter, we use deep neural networks for unsupervised clustering of seismic data. We perform the clustering in a feature space that is simultaneously optimized with the clustering assignment, resulting in learned feature representations… read more here.

Keywords: seismic signals; clustering seismic; deep convolutional; unsupervised clustering ... See more keywords

Anomaly Detection in Public Street Lighting Data Using Unsupervised Clustering

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recommendations! Published in 2024 at "IEEE Transactions on Consumer Electronics"

DOI: 10.1109/tce.2024.3354189

Abstract: The digitization of the energy industry enables the collection and analysis of vast amounts of consumption data for improved decision-making and efficient energy resource utilization. This big data represents an opportunity to address data quality… read more here.

Keywords: public street; unsupervised clustering; street lighting; anomaly detection ... See more keywords