Transfer learning for image classification using pre-trained models like ResNet50, ResNet100, EfficientNetB0, and VGG16 in Keras. Fine-tunes the last layers, applies image augmentation, and evaluates with Precision, Recall, AUC, F1 score, and early stopping for improved performance.
deep-learning keras batch-normalization image-classification regularization transfer-learning vgg16 image-augmentation multiclass-classification adam-optimizer resnet50 early-stopping data-pre-processing relu-activation efficientnetb0 resnet100 precision-recall-auc-f1-score
-
Updated
Jan 9, 2025 - Jupyter Notebook