The application relates to the technical field of topographic analysis, in particular to a
saddle point extraction method, device, equipment, storage medium and program product, wherein the method comprises the following steps: acquiring DEM data for topographic
saddle extraction; based on a preset positive and negative
topography method, extracting a candidate
saddle point set from the DEM data, and extracting a plurality of topographic features of each candidate saddle point in the candidate saddle
point set at a plurality of scales; inputting the plurality of topographic features of each candidate saddle point at the plurality of scales into a pre-established
convolutional neural network for multi-scale topographic
feature fusion, and removing false saddle points in the candidate saddle
point set according to an output result to obtain a final saddle point. Therefore, by combining the positive and negative
topography method and the multi-scale
feature fusion convolutional neural network, the problems of excessive false saddle points when the positive and negative
topography method extracts saddle points are solved, the extraction precision and accuracy of the saddle points are improved, and intelligent analysis and identification of topography are promoted.