Results 151 to 160 of about 55,134 (231)
Test case sampling optimization for safety validation of automated driving systems. [PDF]
Qian C, Xu J, Xing X, Guo F.
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Protein FID: improved evaluation of protein structure generative models. [PDF]
Faltings F +3 more
europepmc +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Application of Bivariate Reproducing Kernel-Based Best Interpolation Method in Electrical Tomography. [PDF]
Tan Y +5 more
europepmc +1 more source
Device‐Level Implementation of Reservoir Computing With Memristors
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
Estimation of space-time self-exciting point process models using multi-dimensional Gaussian-type exponent approximation. [PDF]
Nketiah EA, Li C, Yang W, Jing Y, Guo P.
europepmc +1 more source
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov +8 more
wiley +1 more source
GWKBR: a novel method integrating machine learning and Bayesian inference framework to improve genomic prediction accuracy. [PDF]
Wang X, Jiang J, Zhang Z, Zhang Y.
europepmc +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source

