MultiPert: An adversarial alignment and dual attention framework for single-cell multi-omics perturbation prediction. [PDF]
Zhao M +5 more
europepmc +1 more source
Deep learning‐driven methods for fluorescence imaging denoising
This review evaluates data‐driven deep learning denoising methods that overcome conventional limitations through effective feature extraction and nonlinear modeling. Focusing on fluorescence imaging acquisition under photon‐limited conditions, we delineate cutting‐edge architectures, including supervised learning, unsupervised learning, zero‐shot ...
Xinyu Lu +7 more
wiley +1 more source
Robust detection framework for adversarial threats in Autonomous Vehicle Platooning. [PDF]
Ness S.
europepmc +1 more source
Major Cybersecurity Breaches: Shaping Corporate Cybersecurity Policies and Closing the Gaps
ABSTRACT As digitalization accelerates, cybercrime has intensified in both scale and impact over the past two decades. This study aims to critically examine major cybersecurity events, assess them through the lens of routine activity theory, examine insight from three other established criminological and organizational theories, and address central ...
Laura K. Rickett, Deborah Smith
wiley +1 more source
Trustworthy AI for medical decisions: Adversarially robust and fair machine learning prediction for Parkinson's disease. [PDF]
Muhammad J +4 more
europepmc +1 more source
Deep Learning Integration in Optical Microscopy: Advancements and Applications
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari +5 more
wiley +1 more source
Point cloud generation adversarial network based on self-attention and curvature. [PDF]
Sun F +5 more
europepmc +1 more source
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster +5 more
wiley +1 more source
Particle swarm optimized deep learning for jamming detection and throughput enhancement in cognitive radio networks. [PDF]
Imran M +6 more
europepmc +1 more source

