Dataset and Code for Fine-tuning Neural Networks via Transfer Learning on Image Classification Tasks

The final fully connected layer of 1000 units was replaced with an 8-unit layer to fit the specific classification tasks in this study. The models were fine-tuned with a custom dataset to optimize performance for categorization, while core layers remained unchanged.

Fine-tuning was conducted across the network based on the configurations of pre-existing model parameters. This process aimed at enhancing the model's adaptability for specialized tasks.