https://www.selleckchem.com/products/KU-60019.html
A total number of 3104 data are obtained from simulation and experiments, with 2480 simulated signals for training the CNN model and the remaining 620 simulated data together with 4 experimental signals for verifying the performance of the proposed algorithm. This approach achieves the prediction accuracy of 98.5% on validation set, particularly with the prediction accuracy of 100% for the 4 experimental data. This work proves the feasibility and reliability of the proposed method for quantifying the width of subsurface defects and can
Me gusta
Comentario
Compartir
