Multidimensional data-driven classification of emission-line galaxies
Sign Up to like & getrecommendations! Published in 2019 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stz330
Abstract: We propose a new soft clustering scheme for classifying galaxies in different activity classes using simultaneously 4 emission-line ratios; log([NII ]/Ha), log([SII]/Ha), log([OI]/Ha) and log([OIII]/Hb). We fit 20 multivariate Gaussian distributions to the 4-dimensional distribution… read more here.
Keywords: classification; emission line; soft clustering; clustering scheme ... See more keywords
Federated Learning With Soft Clustering
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DOI: 10.1109/jiot.2021.3113927
Abstract: In this article, we consider the problem of federated learning (FL) with training data that are non independent and identically distributed (non-IID) across the clients. To cope with data heterogeneity, an iterative federated clustering algorithm… read more here.
Keywords: federated learning; soft clustering; learning soft;
Edge-Preserving Image Filtering Based on Soft Clustering
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3124291
Abstract: Edge-preserving image filtering is an essential task in computational photography and imaging. In this paper, we propose a simple yet effective global edge-preserving filter based on soft clustering, and we propose a novel soft clustering… read more here.
Keywords: edge preserving; soft clustering; proposed filter; preserving image ... See more keywords
Soft-clustering Technique for Fingerprint-based Localization
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DOI: 10.18494/sam.2018.1844
Abstract: In this paper, the soft-clustering algorithm for the fingerprint-based localization technique is proposed. In an indoor environment, the fingerprint-based localization technique is usually employed since it can deal with signal fluctuation. Its basic principle is… read more here.
Keywords: technique; fingerprint based; soft clustering; fingerprint ... See more keywords
A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks
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DOI: 10.3390/agronomy11040740
Abstract: Detecting socio-ecological boundaries in traditional rural landscapes is very important for the planning and sustainability of these landscapes. Most of the traditional methods to detect ecological boundaries have two major shortcomings: they are unable to… read more here.
Keywords: landscape; ecological boundaries; approach; bayesian networks ... See more keywords