Results 191 to 200 of about 60,338 (274)

DEEP‐DISORDER: Motion Correction in 3D MRI via Segment Reconstruction and Registration

NMR in Biomedicine, Volume 39, Issue 5, May 2026.
This work presents a retrospective motion correction framework for 3D MRI. A motion‐corrupted acquisition is split into tiny k‐space segments, and for each a neural network reconstructs a rough anatomical image. These reconstructions are aligned using groupwise registration, yielding one set of estimated motion parameters per segment.
Laurens Beljaards, Martijn Nagtegaal, Chinmay Rao, Yiming Dong, Matthias J. P. van Osch, Nicola Pezzotti, Mariya Doneva, Marius Staring   +7 more
wiley   +1 more source

MedScanGAN: Synthetic PET & CT Scan Generation Using Conditional Generative Adversarial Networks for Medical AI Data Augmentation. [PDF]

Bioengineering (Basel)
Samaras AD, Apostolopoulos ID, Papandrianos N.   +2 more
europepmc   +1 more source

Why Autonomous Vehicles Are Not Ready Yet: A Multi‐Disciplinary Review of Problems, Attempted Solutions, and Future Directions

Journal of Field Robotics, Volume 43, Issue 3, Page 2254-2341, May 2026.
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong, Massimiliano Cappuccio, Fady Alnajjar, Luqman Ali, Hamad Al Jassmi, Essam Debie, Milad Ghasrikhouzani, Alessandro Lanteri, Tate McGregor, Oleksandra Molloy, Alice Plebe, Michael Regan, Eduardo Sandoval, Dongmo Zhang   +13 more
wiley   +1 more source

AI‐Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 3, May 2026.
ABSTRACT Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions that traditional methods miss. This systematic review evaluates the application, performance, and methodological characteristics of AI‐enabled imaging for pathogen detection, including its impact
MeiLi Papa, Gillian Kuehnle, Yoo Jung (Erika) Oh, Jiyoon Yi   +3 more
wiley   +1 more source

Evaluating gait system vulnerabilities through PPO and GAN-generated adversarial attacks. [PDF]

Sci Rep
Saoudi EM, Jaafari J, Jai Andaloussi S.
europepmc   +1 more source

Generative neural networks for experimental manipulation: Examining dominance‐trustworthiness face impressions with data‐efficient models

British Journal of Psychology, Volume 117, Issue 2, Page 636-655, May 2026.
Abstract An important development in the study of face impressions was the introduction of dominance and trustworthiness as the primary and potentially orthogonal traits judged from faces. We test competing predictions of recent accounts that address evidence against the independence of these judgements. To this end we develop a version of recent ‘deep
Adam Sobieszek, Maciej Siemiątkowski, Kamil K. Imbir   +2 more
wiley   +1 more source

Enhanced cybersecurity threat detection using novel tri-metaheuristic loss functions in generative adversarial networks with adaptive attention preservation for network traffic augmentation. [PDF]

Sci Rep
Khalil HM, Elrefaiy A, Elbaz M, Loey M.
europepmc   +1 more source

The state of modelling face processing in humans with deep learning

British Journal of Psychology, Volume 117, Issue 2, Page 656-676, May 2026.
Abstract Deep learning models trained for facial recognition now surpass the highest performing human participants. Recent evidence suggests that they also model some qualitative aspects of face processing in humans. This review compares the current understanding of deep learning models with psychological models of the face processing system ...
P. Jonathon Phillips, David White
wiley   +1 more source

Super-Resolution pedestrian re-identification method based on bidirectional generative adversarial network. [PDF]

PLoS One
Wang Y, Wu Y.
europepmc   +1 more source

Imbalance‐Aware Credit Card Fraud Detection Using Multi‐Autoencoders and Generative Ensemble Learning

Expert Systems, Volume 43, Issue 5, May 2026.
ABSTRACT Credit card fraud detection remains a challenging research problem due to the class imbalance issue caused by the rarity of fraudulent transactions. Classical oversampling techniques such as SMOTE, ADASYN and their variants help balance data but do not reflect the nonlinear structure of real‐world fraud, leading to poor generalization.
Sultan Alharbi, Khalid Alahmadi, Xianzhi Wang   +2 more
wiley   +1 more source