Results 71 to 80 of about 152,595 (295)
Tools for analysing fuzzy clusters of sequences data [PDF]
BACKGROUND: Sequence analysis is a set of tools increasingly used in demography and other social sciences to analyse longitudinal categorical data. Typically, single (e.g., education trajectories) or multiple parallel temporal processes (e.g., work and ...
Raffaella Piccarreta +1 more
doaj +1 more source
Improvement of the ANFIS-based wave predictor models by the Particle Swarm Optimization
In this paper, the Particle Swarm Optimization (PSO) algorithm is employed to deal with the Adaptive Network based Fuzzy Inference System (ANFIS) model drawbacks in prediction of wind –driven waves.
Morteza Zanganeh
doaj +1 more source
Performance characterization of clustering algorithms for colour image segmentation [PDF]
This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation ...
Ghita, Ovidiu +2 more
core
Quantum sensing reveals intricate patterns linking endo‐lysosomal maturation to cardiac fibrosis progression, highlighting complexity in cellular remodeling. This study investigates fibroblast‐to‐myofibroblast transition under cell aging, stiffness, and TGF‐β stimulation, comparing nanodiamond uptake, endo‐lysosomal dynamics, and free radical ...
Aldona Mzyk +3 more
wiley +1 more source
Cephalopod‐inspired photonic microparticles with dynamic structural coloration are fabricated via confined self‐assembly of linear block copolymers into ellipsoids containing stacked lamellae. Embedded superparamagnetic nanoparticles enable rapid magnetic alignment, restoring vivid, angle‐dependent color.
Gianluca Mazzotta +8 more
wiley +1 more source
Color Image Segmentation Using Fuzzy C-Regression Model
Image segmentation is one important process in image analysis and computer vision and is a valuable tool that can be applied in fields of image processing, health care, remote sensing, and traffic image detection. Given the lack of prior knowledge of the
Min Chen, Simone A. Ludwig
doaj +1 more source
Robust Self-Sparse Fuzzy Clustering for Image Segmentation
Traditional fuzzy clustering algorithms suffer from two problems in image segmentations. One is that these algorithms are sensitive to outliers due to the non-sparsity of fuzzy memberships.
Xiaohong Jia +5 more
doaj +1 more source
Fuzzy Image Segmentation using Suppressed Fuzzy C-Means Clustering (SFCM) [PDF]
Clustering algorithms are highly dependent on the features used and the type of the objects in a particular image. By considering object similar surface variations (SSV) as well as the arbitrariness of the fuzzy c-means (FCM) algorithm for pixel location,
Ali, Ameer +2 more
core
Beyond the Edge: Charge‐Transfer Excitons in Organic Donor‐Acceptor Cocrystals
Complex excitonic landscapes in acene–perfluoroacene cocrystals are unveiled by polarization‐resolved optical spectroscopy and many‐body theory. This systematic study of a prototypical model system for weakly interacting donor–acceptor compounds challenges common views of charge‐transfer excitons, providing a refined conceptual framework for ...
Sebastian Anhäuser +6 more
wiley +1 more source
Adaptive Fuzzy Clustering [PDF]
Classifying large datasets without any a-priori information poses a problem especially in the field of bioinformatics. In this work, we explore the task of classifying hundreds of thousands of cell assay images obtained by a high-throughput screening camera. The goal is to label a few selected examples by hand and to automatically label the rest of the
Cebron, Nicolas, Berthold, Michael R.
openaire +2 more sources

