Neural style transfer is a computational framework that merges the content of one image with the artistic style of another, utilising deep learning techniques to generate novel visual outputs.
Recent advances in deep learning have revolutionised the way we interpret and classify artistic styles, bridging the gap between the humanities and data science. By leveraging sophisticated neural ...
The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...
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