Results 171 to 180 of about 2,661 (306)

Accurate and Anti‐Interference Control of Computer Vision‐Assisted Light‐Driven Liquid Crystal Elastomer Actuator

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article introduces a computer vision‐assisted control strategy for light‐driven liquid crystal elastomer actuators. Through negative feedback regulation, the liquid crystal elastomer actuator exhibits accurate and stable bending deformation in complex environments.
Wei Zhang   +6 more
wiley   +1 more source

Gaussian Mixture Model‐Based Data Association Incorporating a Deep Learning Network for Multivehicle Tracking and Detection in Autonomous Driving Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a real‐time light detection and ranging‐camera fusion framework for vehicle detection and tracking. Using a Gaussian mixture model‐based association and improved affinity metrics, the method enhances tracking reliability in dynamic conditions.
Muhammad Adeel Altaf, Min Young Kim
wiley   +1 more source

Memory‐Reduced Convolutional Neural Network for Fast Phase Hologram Generation

open access: yesAdvanced Intelligent Systems, EarlyView.
This article reports a lightweight convolutional neural network framework using INT8 quantization to efficiently generate 3D computer‐generated holograms from a single 2D image. The quantized model reduces memory usage and computational cost, accelerates inference speed, and maintains high output quality, enabling real‐time holographic display on low ...
Chenliang Chang   +6 more
wiley   +1 more source

Machine Learning‐Based Standard Compact Model Binning Parameter Extraction Methodology for Integrated Circuit Design of Next‐Generation Semiconductor Devices

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a neural network‐based methodology for Berkeley Short‐Channel IGFET Model–Common Multi‐Gate parameter extraction of gate‐all‐around field effect transistors, integrating binning adaptive sampling and transformer neural networks to efficiently capture current–voltage and capacitance–voltage characteristics.
Jaeweon Kang   +4 more
wiley   +1 more source

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