Image Dataset and Experimental Results for Aesthetic Neural Style Transfer

This dataset accompanies the research paper "Hybrid Approaches to Dynamic Image Style Transfer for Aesthetic Innovation". It includes content images, style images, and experimental results related to neural style transfer. The dataset is structured as follows:

Content_Images/ – Contains 17 images used as content inputs for style transfer.

Style_Images/ – Contains 16 images representing artistic styles applied to the content images.

Results_and_Discussions/ – Includes:

Total Loss on Iterations: A graphical representation of the loss values over multiple iterations.

Total Loss Values for Foreground and Background: Numerical loss data for both foreground and background across multiple iterations.

Execution logs and loss data from the experiment.

Merged images of foreground and background for 15 iterations.

Usage Notes

This dataset can be used for research and development in neural style transfer, deep learning-based image transformation, and aesthetic enhancement techniques. It provides insights into loss progression over iterations, helping researchers analyze the effectiveness of different style transfer approaches.