LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "physics guided" as a keyword



Engineered Nucleotide Chemicapacitive Microsensor Array Augmented with Physics-Guided Machine Learning for High-Throughput Screening of Cannabidiol.

Sign Up to like & get
recommendations! Published in 2022 at "Small"

DOI: 10.1002/smll.202107659

Abstract: The recent legalization of cannabidiol (CBD) to treat neurological conditions such as epilepsy has sparked rising interest across global pharmaceuticals and synthetic biology industries to engineer microbes for sustainable synthetic production of medicinal CBD. Since… read more here.

Keywords: physics; cannabidiol; high throughput; physics guided ... See more keywords

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

Sign Up to like & get
recommendations! Published in 2021 at "Physics of Fluids"

DOI: 10.1063/5.0053349

Abstract: The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the… read more here.

Keywords: physics guided; framework; data driven; physics ... See more keywords

A physics-guided modular deep-learning based automated framework for tumor segmentation in PET.

Sign Up to like & get
recommendations! Published in 2020 at "Physics in medicine and biology"

DOI: 10.1088/1361-6560/ab8535

Abstract: An important need exists for reliable PET tumor-segmentation methods for tasks such as PET-based radiation-therapy planning and reliable quantification of volumetric and radiomic features. To address this need, we propose an automated physics-guided deep-learning-based three-module… read more here.

Keywords: physics guided; framework; tumor segmentation; physics ... See more keywords

A Physics-Guided Data-Driven Feedforward Tracking Controller for Systems With Unmodeled Dynamics—Applied to 3D Printing

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2023.3244194

Abstract: A hybrid (i.e., physics-guided data-driven) feedforward tracking controller is proposed for systems with unmodeled linear or nonlinear dynamics. The proposed controller is based on the filtered basis functions (FBF) approach, and hence called a hybrid… read more here.

Keywords: physics; controller; fbf controller; data driven ... See more keywords

Single Remote Sensing Image Dehazing Using Gaussian and Physics-Guided Process

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2022.3177257

Abstract: Remote sensing (RS) dehazing is a challenging task since various haze distributions severely degrade the image quality. Recent learning-based methods achieve dramatic performance for RS dehazing; however, previous ways are limited to their generality using… read more here.

Keywords: remote sensing; physics; gaussian physics; physics guided ... See more keywords

A Generalizable Physics-Guided Convolutional Neural Network for Irregular Terrain Propagation

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Transactions on Antennas and Propagation"

DOI: 10.1109/tap.2025.3533739

Abstract: The application of split-step parabolic equation (SSPE) methods for radio wave propagation across irregular terrains has gained widespread attention. However, the computational intensity of these methods limits their practical use, leading to the exploration of… read more here.

Keywords: propagation; irregular terrain; physics guided; network ... See more keywords

A Physics-Guided Neural Network Dynamical Model for Droplet-Based Additive Manufacturing

Sign Up to like & get
recommendations! Published in 2022 at "IEEE Transactions on Control Systems Technology"

DOI: 10.1109/tcst.2021.3128422

Abstract: This article develops a physics-guided data-driven model for the height evolution of parts printed in droplet-based additive manufacturing. The proposed model is a convolutional recurrent neural network (ConvRNN) whose structure is derived based on the… read more here.

Keywords: neural network; physics guided; model; geometry ... See more keywords

Physics-Guided Optical Simulation and PSF Analysis for Remote Sensing Images Deblurring

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3426094

Abstract: The presence of blur is prevalent in satellite remote sensing images (RSIs), and its detrimental impact on downstream applications cannot be overlooked. Current deep learning approaches for image deblurring have gained substantial attention due to… read more here.

Keywords: remote sensing; physics guided; rsi deblurring; sensing images ... See more keywords

SocNet: A Physics-Guided Neural Network for Battery State-of-Charge Estimation Robust to Temperature Variations and Sensor Noises

Sign Up to like & get
recommendations! Published in 2025 at "IEEE Transactions on Transportation Electrification"

DOI: 10.1109/tte.2025.3573618

Abstract: For lithium-ion batteries in electric vehicles (EVs), ambient temperature variations and sensor noises affect the accurate estimation of the state of charge (SOC). To achieve both temperature and noise robustness in SOC estimation with an… read more here.

Keywords: temperature; socnet; physics guided; estimation ... See more keywords

Sensorless End-to-End Freehand 3-D Ultrasound Reconstruction With Physics-Guided Deep Learning

Sign Up to like & get
recommendations! Published in 2024 at "IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control"

DOI: 10.1109/tuffc.2024.3465214

Abstract: Three-dimensional ultrasound (3-D US) imaging with freehand scanning is utilized in cardiac, obstetric, abdominal, and vascular examinations. While 3-D US using either a “wobbler” or “matrix” transducer suffers from a small field of view and… read more here.

Keywords: deep learning; reconstruction; freehand; physics guided ... See more keywords

Physics-guided deep learning for skillful wind-wave modeling

Sign Up to like & get
recommendations! Published in 2024 at "Science Advances"

DOI: 10.1126/sciadv.adr3559

Abstract: Modeling sea surface wind-waves is crucial for both scientific research and engineering applications. Nowadays, the most accurate wave models are based on numerical methods, which primarily concern the wave spectrum evolution by solving wave action… read more here.

Keywords: deep learning; wind; guided deep; wave ... See more keywords