Results 181 to 190 of about 9,816 (301)
Adversarial CAM Guidance for Chest X-Ray Classification: Reducing Framing Sensitivity with Mask Supervision. [PDF]
Batchuluun G, Lee SJ, Im SJ, Park KR.
europepmc +1 more source
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom +2 more
wiley +1 more source
AI in Dermato-Oncology: Diagnostic Performance and Prompt-Injection Vulnerability of Vision-Language Models in Dermoscopic Skin Cancer Assessment. [PDF]
Güler I +5 more
europepmc +1 more source
This review focuses on spatial omics, covering the introduction and comparison of technology platforms, explanation and recommendation of algorithm ecology, demonstration of biological applications, and prospect of large models. It aims to help researchers in the interdisciplinary field of spatial omics quickly understand the current situation and ...
Haoxiu Wang +26 more
wiley +1 more source
EUPopLink Country report - Serbia. [PDF]
Lazarevic A, Markovic A.
europepmc +1 more source
Reversible attack based on local visible adversarial perturbation [PDF]
Adding perturbation to images can mislead classification models to produce incorrect results. Based on this, research has exploited adversarial perturbation to protect private images from retrieval by malicious intelligent models.
Zhu, Shaowei +3 more
core
Medical Reasoning With Large Language Models: A Systematic Review and Evaluation
ABSTRACT Large language models (LLMs) have achieved strong performance on medical exam–style tasks, motivating growing interest in their deployment in real‐world clinical settings. However, clinical decision‐making is inherently safety‐critical, context‐dependent, and conducted under evolving evidence.
Xiaohan Ren +6 more
wiley +1 more source
Dual-targeted adversarial noise for 3D point cloud classification model. [PDF]
Lee T, Lee S, Kwon H.
europepmc +1 more source
Mapping the Landscape of Over‐Scanning in CT Imaging: A Scoping Review
Over‐scanning in CT is highly prevalent and contributes to unnecessary radiation exposure, with notable impact on radiosensitive organs. Standardised protocols and AI‐assisted planning show strong potential to optimise scan range and reduce excess dose.
Mo'men Bani‐Ahmad +5 more
wiley +1 more source
Few-shot crop pests and diseases recognition based on adversarial augmentation and task interpolation. [PDF]
Wang K, Fei X, Su L, Fang T, Shen H.
europepmc +1 more source

