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
Automated <i>Mycobacterium tuberculosis</i> Detection in Multivariant Digitized Ziehl-Neelsen Staining Using Faster R-CNN Method. [PDF]
Rulaningtyas R +7 more
europepmc +1 more source
A multi-scale approach to detecting standing dead trees in UAV RGB images based on improved faster R-CNN. [PDF]
Jiang X +5 more
europepmc +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
Domain-adaptive faster R-CNN for non-PPE identification on construction sites from body-worn and general images. [PDF]
Wang S.
europepmc +1 more source
Accurate detection for dental implant and peri-implant tissue by transfer learning of faster R-CNN: a diagnostic accuracy study. [PDF]
Jang WS +6 more
europepmc +1 more source
Interpretable Short‐Term Electric Load Forecasting
A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola +6 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
Improved faster R-CNN for steel surface defect detection in industrial quality control. [PDF]
Leng Y, Liu J.
europepmc +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

