Results 221 to 230 of about 105,541 (300)

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

Enhanced significant wave height prediction in the Southern Ocean using an ANFIS model optimized with subtractive clustering. [PDF]

Sci Rep
Hakimi A, Farjami H.
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

A circular economy based nonlinear corrugated waste management system using Fermatean bipolar hesitant fuzzy logic. [PDF]

Sci Rep
Chaudhary S, Saha AK, Sharma MK.
europepmc   +1 more source

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

A novel multi objective grey wolf optimization fuzzy miner for process discovery: Incorporating robustness and explainability in model evaluation. [PDF]

PLoS One
Salehi M, Khayami R, Mirmozaffari M.
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

Enhancing travel advisory zones for autonomous vehicles using interval-valued pythagorean fuzzy Yager-based decision-making. [PDF]

Sci Rep
Nawaz S, Razaq A, Alhamzi G, Baidar AW.
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

Unveiling cost reduction potential of carbon capture and storage clusters in China under multiple uncertainties. [PDF]

iScience
Wang Y, Li J, Zhang X, Li K, Fan JL, Xiang X, Hou Y.   +6 more
europepmc   +1 more source