Application of Obstacle Automatic Recognition Algorithm in Geometry System Design
DOI:
https://doi.org/10.54097/2kv6e074Keywords:
Obstacle Recognition, Mean Clustering, Support Vector Machine, Geometry System.Abstract
In seismic data acquisition, surface obstacles significantly impact the collection of effective information by affecting the uniformity of source placement or causing missing shots due to the inability to traverse large towns, aquaculture areas, rivers, lakes, and other obstructions. Understanding the distribution ranges of these obstacles allows for adjustments in geometry systems, thereby improving efficiency. This paper discusses several typical satellite image-based automatic obstacle recognition methods, with a focus on detailed explanations of the principles of mean clustering and support vector machines, as well as an analysis of their practical application characteristics. These methods play a crucial role in greatly enhancing productivity.
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