Results 201 to 210 of about 332,624 (268)
Sustainable design of organic solar cells utilized machine and deep learning. [PDF]
Mohyeldien OM +2 more
europepmc +1 more source
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley +1 more source
Intelligent diagnosis method for river and lake ecosystem health based on improved slime mold algorithm-optimized SVR. [PDF]
Chi R, Da Y, Li W, Wen D.
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
Tactile Sensor-Based Body Center of Pressure Estimation System Using Supervised Deep Learning Models. [PDF]
Baik J, Choi Y, Kim KJ, Park YJ, Lee H.
europepmc +1 more source
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang +4 more
wiley +1 more source
Evaluating machine learning models for estimating evapotranspiration in Colombia's Cauca River Valley. [PDF]
Rueda Cadavid JF +4 more
europepmc +1 more source
This article develops a soft magnetic sensor array to extract 3D and distributional muscle deformations, which has highly consistent measurements in amphibious environments, robustness to hydraulic pressure, and about 200 ms faster response than an inertial measurement unit, achieving over 98% classification accuracy and below 3% phase estimation ...
Yuchao Liu +8 more
wiley +1 more source
A high-resolution global leaf chlorophyll content product using the Sentinel-2 data. [PDF]
Zhang H +10 more
europepmc +1 more source
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley +1 more source

