Improved fuzzy C-means clustering in the process of exudates detection using mathematical morphology
Sign Up to like & getrecommendations! Published in 2018 at "Soft Computing"
DOI: 10.1007/s00500-017-2532-8
Abstract: Exudates are a common complication of diabetic retinopathy and the leading cause of blindness in the developing countries, especially in Thailand. The digital retinal images are usually interpreted visually by an expert ophthalmologist in order… read more here.
Keywords: means clustering; exudates detection; process exudates; mathematical morphology ... See more keywords
Modified dynamic fuzzy c-means clustering algorithm – Application in dynamic customer segmentation
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-019-01626-x
Abstract: The dynamic customer segmentation (DCS) is a useful tool for managers in implementing marketing strategies by observing dynamic changes that are happening in the customer segments over time. The Crespo’s dynamic fuzzy c -means (CDFCM)… read more here.
Keywords: fuzzy means; dynamic customer; mdfcm algorithm; dynamic fuzzy ... See more keywords
Fuzzy C-Means Cluster Analysis Based on Variable Length String Genetic Algorithm for the Grouping of Rock Discontinuity Sets
Sign Up to like & getrecommendations! Published in 2020 at "Ksce Journal of Civil Engineering"
DOI: 10.1007/s12205-020-2188-2
Abstract: Discontinuities have huge impact on civil and mining engineering. To understand the spatial features of discontinuities, it is common to group them into different sets based on orientation. In this paper, a new algorithm is… read more here.
Keywords: variable length; fuzzy means; new method; discontinuity sets ... See more keywords
Flow visualization and analysis of thermal distribution for the nanofluid by the integration of fuzzy c-means clustering ANFIS structure and CFD methods
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Visualization"
DOI: 10.1007/s12650-019-00614-0
Abstract: Abstract A nanofluid containing copper (Cu) nanoparticles was simulated in a rectangular cavity using computational fluid dynamic (CFD). The upper and lower walls of the cavity were adiabatic, while the right and left walls had… read more here.
Keywords: means clustering; anfis method; cfd; fuzzy means ... See more keywords
Improved fuzzy C-means algorithm based on density peak
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-019-00993-8
Abstract: Fuzzy C-means (FCM) algorithm is a fuzzy clustering algorithm based on objective function compared with typical “hard clustering” such as k-means algorithm. FCM algorithm calculates the membership degree of each sample to all classes and… read more here.
Keywords: fuzzy means; density; algorithm based; algorithm ... See more keywords
Gaussian Collaborative Fuzzy C-Means Clustering
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Fuzzy Systems"
DOI: 10.1007/s40815-021-01090-1
Abstract: For most FCM-based fuzzy clustering algorithms, several problems, such as noise, non-spherical clusters, and size-imbalanced clusters, are difficult to solve. Different fuzzy clustering algorithms are developed to deal with these problems from different perspectives. However,… read more here.
Keywords: gaussian collaborative; fuzzy clustering; collaborative fuzzy; fuzzy ... See more keywords
Retinal Blood Vessel Segmentation by Using Matched Filtering and Fuzzy C-means Clustering with Integrated Level Set Method for Diabetic Retinopathy Assessment
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Medical and Biological Engineering"
DOI: 10.1007/s40846-018-0454-2
Abstract: BackgroundThe condition of blood vessel network in the retina is an essential part of diagnosing various problems associated with eyes, such as diabetic retinopathy.MethodsIn this study, an automatic retinal vessel segmentation utilising fuzzy c-means clustering… read more here.
Keywords: vessel segmentation; segmentation; blood vessel; vessel ... See more keywords
Pothole detection on asphalt pavements from 2D-colour pothole images using fuzzy c-means clustering and morphological reconstruction
Sign Up to like & getrecommendations! Published in 2017 at "Automation in Construction"
DOI: 10.1016/j.autcon.2017.08.017
Abstract: Abstract In general, potholes on asphalt pavements can be detected and represented in 2D and 3D. However, pothole detections through 3D imaging and image reconstructions have proven to be expensive in terms of acquisition equipment… read more here.
Keywords: fuzzy means; pothole detection; detection; image ... See more keywords
Determination of the typical load profile of industry tasks using fuzzy C-Means
Sign Up to like & getrecommendations! Published in 2020 at "Energy Reports"
DOI: 10.1016/j.egyr.2020.11.094
Abstract: Abstract This paper aims to promote the importance and advantages that the clustering method brings to the world of industry, making it possible to increase production efficiency and to manage the energy resources available better.… read more here.
Keywords: fuzzy means; task; typical load; load profile ... See more keywords
A fuzzy c-means clustering approach for haplotype reconstruction based on minimum error correction
Sign Up to like & getrecommendations! Published in 2021 at "Informatics in Medicine Unlocked"
DOI: 10.1016/j.imu.2021.100646
Abstract: Abstract Studying human genetic evolution has attracted considerable attention. Haplotypes determination provides key information about human genetics, and facilitates understanding probable causal relations between traits and diseases. In general, experimental methods of haplotypes reconstruction are… read more here.
Keywords: reconstruction; means clustering; input fragments; fuzzy means ... See more keywords
Bayesian distance metric learning for discriminative fuzzy c-means clustering
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.08.071
Abstract: Abstract A great number of machine learning algorithms strongly depend on the underlying distance metric for representing the important correlations of input data. Distance metric learning is defined as learning an appropriate similarity or distance… read more here.
Keywords: metric learning; means clustering; distance metric; bayesian distance ... See more keywords