Results 141 to 150 of about 215,279 (299)

Seeing Through the Face: Robust Facial Diagnosis Enhanced by Landmark Detection and Pose Normalization

Advanced Intelligent Systems, EarlyView.
This study proposes a robust, generalizable new approach for facial type diagnosis. Based on landmark detection and pose normalization, a 94.7% diagnostic accuracy is achieved by Combined Heatmap Regression and Coordinate Regression network. This research makes the AI‐generated preliminary diagnosis more interpretable and reducing the impact of ...
Qianyang Xie, Zixian Jiao, Guo Bai, Huimin Zhu, Dahe Zhang, Hui Li, Haixia Lu, Xin Nie, Qing Li, Duohong Zou, Zhiguo Yin, Peilun Li, Chi Yang   +12 more
wiley   +1 more source

Intelligent Operator‐Independent Flexibility in Robotic Non‐Destructive Evaluation

Advanced Intelligent Systems, EarlyView.
Non‐destructive evaluation of high‐value components remains a manufacturing bottleneck due to rigid robotic calibration and fixturing. This study presents a flexible, adaptable system integrating 3D vision and force‐position control with a collaborative KUKA LBR robot. The geometry‐agnostic system enables pose‐independent ultrasonic inspection, detects
Amine Hifi, Randika K. W. Vithanage, Shaun McKnight, Vedran Tunukovic, Ewan Nicolson, Rylan Gomes, Alastair Poole, Ehsan Mohseni, Stephen Gareth Pierce, Charles MacLoed, Tom O’Hare, Gavin Munro   +11 more
wiley   +1 more source

EASE: Examination of Anomalous Self-Experience

, 2020
The Examination of Anomalous Self-Experience (EASE) is a symptom checklist for semistructured, phenomenological exploration of experiential or subjective anomalies that may be considered as disorders of basic or ‘minimal’ self-awareness. The EASE is developed on the basis of self-descriptions obtained from patients suffering from schizophrenia spectrum
openaire   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

Conceptual and Empirical Variations in Relations Between Spirituality and Mental Health (Review of "Spirituality and Mental Health Across Cultures")

Journal of Anomalous Experience and Cognition, 2022
Ralph W. Hood Jr.
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +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

Open Peer Comment to “Anomalous Cognition: An Umbrella Review of the Meta-Analytic Evidence”

Journal of Anomalous Experience and Cognition, 2021
Stefan Schmidt
doaj   +1 more source

Multimodality Imaging of Anomalous Left Main Coronary Artery From the Right Sinus of Valsalva. [PDF]

JACC Case Rep
Ibrahim R, Suppah M, Almakadma AH, Martinez F, Chan E.   +4 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