Results 161 to 170 of about 152,595 (295)

Fuzzy Clustering and Fuzzy Clustering Models

Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 2019
openaire   +2 more sources

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Application of Fuzzy Clustering Model in the Classification of Sports Training Movements. [PDF]

Comput Intell Neurosci, 2022
Song B.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Combining multifaceted aspects of technology innovations through fuzzy clustering of multilayer networks. [PDF]

PLoS One
Cerqueti R, Ferraro G, Mattera R, Storani S.   +3 more
europepmc   +1 more source

Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering. [PDF]

PeerJ Comput Sci, 2022
Cebeci Z, Cebeci C, Tahtali Y, Bayyurt L.   +3 more
europepmc   +1 more source

Fuzzy clustering

, 2016
Stato dell'arte nella teoria e nell'applicazione della metodologia ...
openaire   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Delineating soil fertility management zones using geostatistics and fuzzy clustering in semi-arid maize systems in India. [PDF]

Environ Monit Assess
Bhagwan PV, Anjaiah T, Ravali C, Devi MU, Neelima TL, Chary DS, Chatterjee S.   +6 more
europepmc   +1 more source