Automatic Multi-Label Classification of South China Sea Maps Based on AlexNet Model
[Objective]This paper aims to achieve multi-semantic classification of maps and meet the needs for precise map retrieval and intelligence analysis.[Methods]We designed a map category system and proposed a multi-label map classification strategy.It realized the automatic classification of South China Sea maps based on the AlexNet convolution neural network classification model.[Results]The Fl value of the proposed model is 0.979.This model can effectively realize the multi-label automatic classification of the South China Sea maps.[Limitations]The deep categories of multi-label annotated datasets need to be supplemented.[Conclusions]This paper provides a reference for the semantic-based scientific classification of maps,precise retrieval,and cross-category association.
Map ImageMulti-label ClassificationAlexNet ModelSouth China Sea
NETL
NSTL
万方数据
