Results 151 to 160 of about 11,198,909 (310)
A divisive hierarchical k-means based algorithm for image segmentation
, 2010 In this paper we present a divisive hierarchical method for the analysis and segmentation of visual images. The proposed method is based on the use of the k-means method embedded in a recursive algorithm to obtain a clustering at each node of the ...
Gómez González, Daniel +2 more
core +1 more source
FEBS Letters, EarlyView.Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley +1 more source
A study on learning-augmented k-means clustering
reservedClustering is a practical approach for extracting meaningful information from unstructured data. With the exponential growth of data, it is essential to develop efficient methods for computing clusters.
PEPAJ, MARIA TERESA
core
Semesta Teknika, 2016 The selection process among outstanding students in a department has a big problem. This process is not fair because only involve one criteria and ignore the other criteria.
Asroni Asroni, Ronald Adrian
doaj
A review of unsupervised k-value selection techniques in clustering algorithms
Journal of Industrial Engineering and ManagementPurpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms, which makes them an essential tool when working with large datasets. However, although they are unsupervised tools, they generally require
Ana Pegado-Bardayo +3 more
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Unsupervised classification of epileptic EEG signals with multi scale K-means algorithm
, 2013 Most epileptic EEG classification algorithms are supervised and require large training data sets, which hinders its use in real time applications. This paper proposes an unsupervised multi-scale K-means (MSK-means) algorithm to distinguish epileptic EEG ...
Zhu, Guohun +10 more
core +1 more source
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Face detection based on K-medoids clustering and associated with convolutional neural networks
HeliyonOver the last several years, the COVID-19 epidemic has spread over the globe. People have become used to the novel standard, which involves working from home, chatting online, and keeping oneself clean, to stop the spread of COVID-19.
Potharla Ramadevi, Raja Das
doaj +1 more source
FEBS Letters, EarlyView.CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source