Cross‐Modal Characterization of Thin‐Film MoS2 Using Generative Models
Cross‐modal learning is evaluated using atomic force microscopy (AFM), Raman spectroscopy, and photoluminescence spectroscopy (PL) through unsupervised learning, regression, and autoencoder models. Autoencoder models are used to generate spectroscopy data from the microscopy images.
Isaiah A. Moses +3 more
wiley +1 more source
Clinical outcomes of neobladder or augmentation after cystectomy in locally advanced colorectal cancer involving urinary tract: case series. [PDF]
Lee C, Nam W, Kim CW, Yoon YS, You D.
europepmc +1 more source
Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness
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
A Case Report of Eosinophilic Enteritis Complicated with <i>Klebsiella Pneumoniae</i> Infection in a Chinese Male. [PDF]
Lun H, Sui S, Zhang Z, Jiang M.
europepmc +1 more source
Parametrized Arctangent Sigmoid Function Based Banach Space Valued Neural Network Approximation
George A. Anastassiou
openalex +1 more source
Real‐Time and Rapid Dynamic Missile Identification Utilizing a TiOx Memristor Array
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
Incidental Discovery of a Sigmoid Colon Gastrointestinal Stromal Tumor Mimicking Colitis: A Case Report. [PDF]
Patel N +4 more
europepmc +1 more source
Log-sigmoid Activation Function based MLP Network for Aggregate Classification
Nazrul Fariq Makmor +4 more
openalex +1 more source
A machine learning framework is developed for the inverse design of 4D‐printed active composite plates. It utilizes a forward model to predict shapes from patterns and an inverse model to suggest initial patterns for desired shapes. This framework integrates a genetic algorithm to refine the predicted patterns, ensuring higher accuracy in achieving ...
Teerapong Poltue +4 more
wiley +1 more source
Dataset-Learning Duality and Emergent Criticality. [PDF]
Kukleva E, Vanchurin V.
europepmc +1 more source

