Results 141 to 150 of about 123,697 (193)

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

Coral-YOLO: An Intelligent Optical Vision Sensing Framework for High-Fidelity Marine Habitat Monitoring and Forecasting. [PDF]

Sensors (Basel)
Tao J, Tian H, Huang S, Ye Y, Xiong Y, Huang S, Qin J, Yin Y, Zhang J, Tang Y, Wu J.   +10 more
europepmc   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

Advanced Intelligent Systems, EarlyView.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti, Idilio Drago, Anisa Rula, Devis Bianchini, Federico Cerutti   +4 more
wiley   +1 more source

Digital Surface‐Enhanced Raman Scattering With Event Counting and Spectrum Learning for Label‐Free Protein Quantification

Advanced Intelligent Systems, EarlyView.
A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley   +1 more source

Survey on mathematical modeling of infectious disease dynamics: insights and applications. [PDF]

BMC Infect Dis
Eshtewy NA, Forootani A, Sisi ZA.
europepmc   +1 more source

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

Advanced Intelligent Systems, EarlyView.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin, Rudolf M. Füchslin, Achille Giacometti, Helmut Hauser, Marco Werner   +4 more
wiley   +1 more source

AI-driven virtual cell models in preclinical research: technical pathways, validation mechanisms, and clinical translation potential. [PDF]

NPJ Digit Med
Ma C, Zhang H, Rao Y, Jiang X, Liu B, Sun Z, Song Z, Gao Y, Cui Y, Liu X, Li Z.   +10 more
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

Neural variability in the medial prefrontal cortex contributes to efficient adaptive behavior. [PDF]

Nat Commun
Findling C, Romand-Monnier M, Skvortsova V, Koechlin E.   +3 more
europepmc   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source