Results 141 to 150 of about 4,729 (197)

Divide and Cluster: The DIVINE Framework for Deterministic Top-Down Analysis of Molecular Dynamics Trajectories. [PDF]

J Chem Inf Model
Santos JBW, Chen L, Miranda-Quintana RA.
europepmc   +1 more source

Phenotypic analysis method for 3D reconstruction of eggplant seedlings fused with background purification - based on the improved EggplantPointNet++ model and DBSCAN clustering. [PDF]

Front Plant Sci
Xu J, Dong J, Zhang Z, Zhang Y, Zhang X, Deng C, Li J, Zhong Z, Pan F, Wu H, Fu X.   +10 more
europepmc   +1 more source

Clustering and Interpretability of Residential Electricity Demand Profiles. [PDF]

Sensors (Basel)
Kallel S, Amayri M, Bouguila N.
europepmc   +1 more source

AI-based approach for heart failure readmission prediction using SCG, ECG, and GSR signals. [PDF]

Physiol Meas
Dhar R, Hossen MR, Gamage PT, Sandler RH, Raval NY, Mentz RJ, Mansy HA.   +6 more
europepmc   +1 more source

Evolution of chronic diseases and multimorbidity clusters among the deceased in rural northeast South Africa (2012-2022): Insights from verbal autopsy data

Chironda CT, Chirwa T, Mlambo F, Mupfuti R, Ohene-Kwofie D, Njiro BJ, Bashingwa JJH, Tollman S, Kahn K, Gomez-Olive FX, Kabudula CW.   +10 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

A genetic k-medoids clustering algorithm

Journal of Heuristics, 2006
We propose a hybrid genetic algorithm for k-medoids clustering. A novel heuristic operator is designed and integrated with the genetic algorithm to fine-tune the search. Further, variable length individuals that encode different number of medoids (clusters) are used for evolution with a modified Davies-Bouldin index as a measure of the fitness of the ...
Weiguo Sheng
exaly   +2 more sources

A simple and fast algorithm for K-medoids clustering

Expert Systems With Applications, 2009
This paper proposes a new algorithm for K-medoids clustering which runs like the K-means algorithm and tests several methods for selecting initial medoids. The proposed algorithm calculates the distance matrix once and uses it for finding new medoids at every iterative step.
Chi-Hyuck Jun
exaly   +3 more sources

Convex fuzzy k-medoids clustering

Fuzzy Sets and Systems, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daniel Nobre Pinheiro, Daniel Aloise, Simon J. Blanchard   +2 more
openaire   +1 more source

Video summarization by k-medoid clustering

Proceedings of the 2006 ACM symposium on Applied computing, 2006
In this paper, we propose a video summarization algorithm by multiple extractions of key frames in each shot. This algorithm is based on the k-medoid clustering algorithms to find the best representative frame for each video shot. This algorithm, which is applicable to all types of descriptors, consists of extracting key frames by similarity clustering
Youssef Hadi, Fedwa Essannouni, Rachid Oulad Haj Thami   +2 more
openaire   +1 more source