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Figure 3. Architectural implementation and classification performance analysis of the gradient-thickness SRO morphology classification model. (A) CNN architecture for SRO morphology classification; (B and C) Accuracy curves and loss function trends for the (B) training set and (C) validation set under different weight decay hyperparameters; (D and E) Comparison of accuracy and loss function trends for the (D) training set and (E) validation set between the default and optimized parameter configurations. SRO: SrRuO₃; CNN: convolutional neural network.