Results 191 to 200 of about 512,844 (338)

Collaborative Visual Localization for Modular Self‐Reconfigurable Robots

open access: yesAdvanced Intelligent Systems, EarlyView.
Relative localization in modular self‐reconfigurable robots is challenged by hardware limitations, constrained fields of view, and sensor faults. This paper, based on the SnailBot platform, presents a vision‐based collaborative localization method that combines ArUco markers with learning‐based algorithms to enable robust pose estimation from ...
Guanqi Liang   +4 more
wiley   +1 more source

Predictive Parameters of Dropout During Inhaled Corticosteroid Tapering [PDF]

open access: bronze, 2002
Daniel K.C. Lee   +2 more
openalex   +1 more source

An Intelligent Feature Engineering‐Driven Hybrid Framework for Adversarial Domain Name System Tunneling Detection

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a novel framework that enhances the reliability of DNS traffic monitoring using a hybrid long short‐term memory‐deep neural network (LSMT‐DNN) architecture, enabling robust detection of adversarial DNS tunneling. The proposed framework leverages feature extraction from DNS traffic patterns, including domain request sequences, query ...
Ahmad Almadhor   +5 more
wiley   +1 more source

Explainable AI‐Driven Optimization of Electrode Activation Reduces Power Consumption While Preserving Object Recognition in Retinal Prostheses

open access: yesAdvanced Intelligent Systems, EarlyView.
Explainable artificial intelligence (XAI) guides selective electrode activation in retinal prostheses by emphasizing visually informative regions. XAI‐assisted phosphene generation maintains object recognition performance while significantly reducing stimulation power.
Sein Kim, Hamin Shim, Maesoon Im
wiley   +1 more source

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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