An attempt to generate new bridge types from latent space of denoising
  diffusion Implicit model
Hongjun Zhang
Use denoising diffusion implicit model for bridge-type innovation. The
process of adding noise and denoising to an image can be likened to the process
of a corpse rotting and a detective restoring the scene of a victim being
killed, to help beginners understand. Through an easy-to-understand algebraic
method, derive the function formulas for adding noise and denoising, making it
easier for beginners to master the mathematical principles of the model. Using
symmetric structured image dataset of three-span beam bridge, arch bridge,
cable-stayed bridge and suspension bridge , based on Python programming
language, TensorFlow and Keras deep learning platform framework , denoising
diffusion implicit model is constructed and trained. From the latent space
sampling, new bridge types with asymmetric structures can be generated.
Denoising diffusion implicit model can organically combine different structural
components on the basis of human original bridge types, and create new bridge
types.