Results 201 to 210 of about 2,884,172 (338)

Entropy‐Guided Convolutional Neural Network Classification of Sensor Signals for Real‐Time Surface Quality Monitoring in Direct Laser Interference Patterning

Advanced Intelligent Systems, EarlyView.
Neural‐network pipeline for real‐time DLIP surface‐quality monitoring: spectral entropy of WLI topographies is used to generate interpretable K‐means labels, which are transferred to time‐resolved photodiode traces. A compact dual‐input 1D‐CNN (signal + laser parameters) learns discriminative spatiotemporal features and predicts “OK/NOK” surface ...
Marcelo Daniel Sallese, Ignacio Tabares, Wei Wang, Marcos Soldera, Andrés Fabián Lasagni   +4 more
wiley   +1 more source

Author Correction: Signature-based intrusion detection using machine learning and deep learning approaches empowered with fuzzy clustering. [PDF]

Sci Rep
Ahmed U, Nazir M, Sarwar A, Ali T, Aggoune EM, Shahzad T, Khan MA.   +6 more
europepmc   +1 more source

MTCA‐Net: Multi‐Task Cascade Analysis Network for Real‐Time Sperm Quality Analysis

Advanced Intelligent Systems, EarlyView.
This article proposes MTCA‐Net, a multi‐task cascaded analysis network for real‐time sperm quality assessment in intracytoplasmic sperm injection. The framework integrates detection, tracking, and segmentation modules to jointly analyze sperm morphology and motility.
Jiajin Li, Wenwen Sun, Jun He, Xinyu Fan, Xuecheng Ge, Fengya Lu, Yadan Wang, Yi Wang, Zhiguo Zhang, Qibing Wu, Jinhua Zhou   +10 more
wiley   +1 more source

From Microscale to Nanoscale Shadow Electrochemiluminescence Microscopy

Angewandte Chemie, EarlyView.
In this research we report on the label‐free shadow electrochemiluminescence (shadow ECL) microscopy of microscale and nanoscale objects. By systematically investigating various influencing factors—including optical configuration, electrode activity, frame averaging, exposure time, and particle arrangement—we further confirm the nano‐imaging potential ...
Xiaodan Gou, Hanna Manko, Jasmina Vidic, Laurent Cognet, Jun‐Jie Zhu, Neso Sojic   +5 more
wiley   +2 more sources

Iris Recognition System Using Advanced Segmentation Techniques and Fuzzy Clustering Methods for Robotic Control. [PDF]

J Imaging
Ben Chaabane S, Harrabi R, Seddik H.
europepmc   +1 more source

An Online Weighted Bayesian Fuzzy Clustering Method for Large Medical Data Sets. [PDF]

Comput Intell Neurosci, 2022
Zhang C, Xue J, Gu X.
europepmc   +1 more source

Deformable Attention Multiscale Feature Fusion Network‐Dehaze: An Adaptive Image Dehazing Method Based on Deformable Attention Multiscale Fusion Network

Advanced Intelligent Systems, EarlyView.
This paper presents the deformable attention multiscale feature fusion network‐dehaze adaptive image dehazing network, which integrates three core modules (revised residual shrinkage unit, multiscale attention, cross‐scale feature fusion). It incorporates deformable convolution and multiscale attention mechanisms to address the detail loss issue of ...
Ruipeng Wang, Yajun Chen, Hao Liu, Mingrui Li, Zhiqi Li   +4 more
wiley   +1 more source

Ion‐Lock Storage With Multi‐Logic Circuitry Gated by Polar–Dipolar Interactions in Poly(Ionic Liquids)

Angewandte Chemie, EarlyView.
Precise building block design of poly(ionic liquids) creates an opportunity to achieve ionic conductivity, energy storage, and multi‐value logic in one material while eliminating elaborate fabrication processes. ABSTRACT In these studies, we developed a new generation of polymeric materials capable of electrical energy storage and forming higher‐than ...
Sourav Biswas, Jiahui Liu, Jack Austin, Marek W. Urban   +3 more
wiley   +2 more sources

Characterizing cognitive phenotypes and clinical correlates in type 2 diabetes using fuzzy clustering and decision tree analysis. [PDF]

Sci Rep
Sümbül-Şekerci B, Pasin Ö, Egeli D, Gönenç S, Şekerci A.   +4 more
europepmc   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source