Results 171 to 180 of about 66,224 (345)

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

A Bridge Crack Segmentation Algorithm Based on Fuzzy C-Means Clustering and Feature Fusion. [PDF]

Sensors (Basel)
Yao Y, Zhang Y, Liu Z, Yuan H.
europepmc   +1 more source

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

Advanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty, Antonis Vamvakeros, Samuel J. Cooper   +2 more
wiley   +1 more source

Possibility Fuzzy C-Means Clustering for Expression Invariant Face Recognition

, 2014
Aruna Bhat
openalex   +1 more source

A computational intelligence approach for classifying dental caries in X-ray images using integrated fuzzy C-means clustering with feature reduction and a weighted matrix scheme. [PDF]

Sci Rep
Wisaeng K, Muangmeesri B.
europepmc   +1 more source

Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes

Advanced Intelligent Systems, EarlyView.
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera, Gaurav Duggal, Rolf Müller   +2 more
wiley   +1 more source

Point-of-interest recommender model using geo-tagged photos in accordance with imperialist Fuzzy C-means clustering. [PDF]

PLoS One
Salehi Solaiman Abadi AA, Khamforoosh K, Maihami V.   +2 more
europepmc   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Penerapan Fuzzy C-Means Cluster dalam Pengelompokkan Provinsi Indonesia Menurut Indikator Kesejahteraan Rakyat

, 2019
Nurfidah Dwitiyanti, Noni Selvia, Finata Rastic Andrari   +2 more
openalex   +2 more sources

Cnidaria herd optimized fuzzy C-means clustering enabled deep learning model for lung nodule detection. [PDF]

Front Physiol
Prasada Rao RH, Goswami AD.
europepmc   +1 more source