Results 201 to 210 of about 41,144 (258)
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
This study proposes a novel weighted random forest multimodal fusion method that combines smart glasses and sEMG data for in‐vehicle gesture interaction. It realizes stable performance in dim, occluded, and other constrained scenarios, providing feasible solutions and laying a foundation for universal human–machine interaction.
Wenbo Zhang +8 more
wiley +1 more source
Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu +6 more
wiley +1 more source
An AI‐enabled micromixing framework is developed by integrating cGAN with Bayesian optimization for predictive control of microrobot‐driven flow manipulation. Through this framework, the spatiotemporal evolution of micromixing is learned directly from experimental images, while rapid identification of optimized microrobot actuation strategies is ...
Dineshkumar Loganathan, Chia‐Yuan Chen
wiley +1 more source
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang +4 more
wiley +1 more source
Machine Learning and Deep Learning for Earthquake Monitoring: A Systematic Review of Distributed Acoustic Sensing Applications. [PDF]
Iqbal N +4 more
europepmc +1 more source
A training‐free two‐stage BO–RL framework extracts compact model parameters for a‐IGZO TFTs, reaching BO‐level fitting quality at a constant per‐simulation optimization cost. Bayesian optimization performs exploration and provides an optimized starting point.
Seunghyun Son +4 more
wiley +1 more source
Everything Is Prediction: Modern Machine Learning as Bayesian Inference. [PDF]
Polson NG, Sokolov V, Soyer R.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
This review highlights recent advances in automated iPSC culture systems integrating robotics, advanced imaging, artificial intelligence, and process control. These technologies improve reproducibility, scalability, and quality in cell expansion, differentiation, and real‐time monitoring, while emerging AI‐enabled and closed‐loop approaches offer new ...
Hyoryong Lee +3 more
wiley +1 more source

