While I'm training a tensorflow model, the training keeps gets interrupted at the epoch after completing 80% of the total number of epochs I specified to train for. For example, it will stop training at epoch 81
Microscopic images are captured and then are used to train a network to perform virtual H&E staining. Hence, the quality of the resulting virtual H&E staining will be directly determined by the characteristics of the optical microscope used to capture the images. In the ideal case, the ...
According to the panels the convergence was reached after few epochs of training. Panel (a) of Figure 3 presents the convergence of the cost function (MSE). Please note that the value of the cost function drops quickly as the epochs advance. Panel (b) shows the convergence of the MAE,...
Other parameters, such as the number of epochs and the dataset, will be equalized. The number of paired data used was 1365, divided into training and validation datasets. The selection of the validation dataset was done randomly and the number of datasets to be used for validation was 10. ...
Total electron content (TEC) describes the line-of-sight number of charged particles in the ionosphere, and an increase in TEC corresponds to increasing propagation delays for transionospheric signals. The TEC can be represented by TEC units (TECU), where 1 TECU stands for 1016 free electrons...
Models that show exhibit consistent performance across all datasets are more likely to perform effectively in real-world settings. From the analysis, models such as the LR produced R2 of 0.80–0.83, with RMSE of 33.09–34.77 mg/L, and the SVM produced R2 of 0.80–0.83, with RMSE of 34.40...