The intelligent fault identification method based on multi-source information fusion and deep learning.

Faults represent significant geological structures. Conventional fault identification methods pri-marily rely on the linear features of faults, achieved through the interpretation of remote sensing imagery (RSI). To more accurately enhance the morphological features of faults and achieve their rapid, precise, and intelligent identification, this paper employs a multi-source information fusion method.