Results 81 to 90 of about 2,884,172 (338)
Advanced Healthcare Materials, EarlyView.Cerebral organoids are transforming brain research, yet the field remains fragmented. This comprehensive systematic review maps 738 studies published between 2014 and 2024 to uncover trends, gaps, and opportunities across neuroscience. Introducing OrganoidMap—an interactive, open‐access platform to explore and compare models—this work enables ...
Anna Wolfram +10 more
wiley +1 more source
Fuzzy Image Segmentation using Suppressed Fuzzy C-Means Clustering (SFCM) [PDF]
, 2004 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
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Advanced Healthcare Materials, EarlyView.A human microfluidic blood‐brain barrier (mBBB) model enables spatially resolved comparison of nanoparticle trafficking. Extracellular vesicles (EVs), liposomes, and nanoplastics exhibit distinct transport and disruption behaviors, revealing that membrane composition and uptake pathways govern BBB interaction.
Bryan B. Nguyen +9 more
wiley +1 more source
Color Image Segmentation Using Fuzzy C-Regression Model
Advances in Fuzzy Systems, 2017 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
Advanced Materials, Volume 37, Issue 13, April 2, 2025.A single object with dual properties – degradable and non‐degradable – is fabricated in a single print simply by switching the printing colors. The advanced multi‐material printing is enabled by the combination of a fully wavelength‐orthogonal photoresin and a monochromatic tunable laser printer, paving the way for precise multi‐material ...
Xingyu Wu +5 more
wiley +1 more source
Performance characterization of clustering algorithms for colour image segmentation [PDF]
, 2006 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
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Adaptive Fuzzy Clustering [PDF]
NAFIPS 2006 - 2006 Annual Meeting of the North American Fuzzy Information Processing Society, 2006 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
Advanced Materials, EarlyView.Photo‐rewritable ambipolar organic synapses operating in aqueous environments at low voltage (≤0.4 V) demonstrate bidirectional optical plasticity through photon‐modulated electrochemical doping. The bulk heterojunction device enables both excitatory and inhibitory responses with extended retention time (>130 min).
Xiaoqian Su +14 more
wiley +1 more source
A Fuzzy Granular K-Means Clustering Method Driven by Gaussian Membership Functions
MathematicsThe K-means clustering algorithm is widely applied in various clustering tasks due to its high computational efficiency and simple implementation.
Junjie Huang +4 more
doaj +1 more source
Automatic Feature Set Selection for Merging Image Segmentation Results Using Fuzzy Clustering [PDF]
, 2005 The image segmentation performance of clustering algorithms is highly dependent on the features used and the type of objects contained in the image, which limits the generalization ability of such algorithms.
Ali, Ameer +2 more
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