Results 151 to 160 of about 91,637 (246)

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

Prototypical contrastive learning with patch-based spatio-temporal alignment for multivariate time series anomaly detection. [PDF]

Sci Rep
Yang C, Li X, Xu K, Lin X, Fu G.
europepmc   +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

HIPER-CHAD: Hybrid Integrated Prediction-Error Reconstruction-Based Anomaly Detection for Multivariate Indoor Environmental Time-Series Data. [PDF]

Sensors (Basel)
Widartha VP, Kim CS.
europepmc   +1 more source

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

Advanced 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, Shtwai Alsubai, Monji Mohamed Zaidi, Natalia Kryvinska, Abdullah Al Hejaili, Sidra Abbas   +5 more
wiley   +1 more source

A simulation-based dataset for anomaly detection in hydrogen blend transport networks. [PDF]

Data Brief
Senese A, De Vito S, Esposito E, Villari M, Acampora G, Francia GD, Longobardi A, Monteleone G.   +7 more
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

Unraveling the Dynamics of Oxytocin in Hypothalamic Neurons. [PDF]

Traffic
Aznar-Escolano B, Egorova V, Villanueva J, Gutiérrez LM, González-Vélez V, Gil A, Jurado S.   +6 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