Results 241 to 250 of about 15,368 (325)

Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness

open access: yesAdvanced Intelligent Systems, EarlyView.
True random numbers can protect generative artificial intelligence (GAI) models from attacks. A highly parallel, spin‐transfer torque magnetic tunnel junction‐based system is demonstrated that generates high‐quality, energy‐efficient random numbers.
Youwei Bao, Shuhan Yang, Hyunsoo Yang
wiley   +1 more source

DNA-Inspired Lightweight Cryptographic Algorithm for Secure and Efficient Image Encryption. [PDF]

open access: yesSensors (Basel)
Abdelaal MA   +5 more
europepmc   +1 more source

Real‐Time and Rapid Dynamic Missile Identification Utilizing a TiOx Memristor Array

open access: yesAdvanced Intelligent Systems, EarlyView.
Real‐time missile target identification is demonstrated using an artificial intelligence model based on step‐weighted long–short‐term memory networks and a TiOx memristor array. The approach classifies five projectile types with enhanced early‐stage prediction through data augmentation and custom training strategies. Achieving 94.4% accuracy, the model
Mingyu Kim, Gwanyeong Park, Gunuk Wang
wiley   +1 more source

Degeneracy Sensing Light Detection and Ranging‐Inertial Simultaneous Localization and Mapping with Dual‐Layer Resistant Odometry and Scan‐Context Loop‐Closure Detection Backend in Diverse Environments

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper presents a degeneracy‐aware light detection and ranging (LiDAR)‐inertial framework that enhances LiDAR simultaneous localization and mapping performance in challenging environments. The proposed system integrates a dual‐layer robust odometry frontend with a Scan‐Context‐based loop‐closure detection backend.
Haoming Yang   +4 more
wiley   +1 more source

Disentangling Coincident Cell Events Using Deep Transfer Learning and Compressive Sensing

open access: yesAdvanced Intelligent Systems, EarlyView.
Overlapping cells during detection distort single‐cell measurements and reduce diagnostic accuracy. A hybrid framework combining a fully convolutional neural network with compressive sensing to disentangle overlapping signals directly from raw time‐series data is presented.
Moritz Leuthner   +2 more
wiley   +1 more source

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