Camouflage object semantic segmentation method and system based on decision-level feature fusion modeling, medium and electronic equipment

The invention provides a camouflage object semantic segmentation method based on decision-level feature fusion modeling, and the method is characterized in that the method comprises the steps: S1, inputting a to-be-segmented image, carrying out the supervised training of a model through a camouflage object image with a pixel-level label, and obtaining the extraction result of the multi-scale features of the to-be-segmented image through the supervised training; s2, based on the extraction result of the multi-scale features, processing a camouflage object in the to-be-segmented image by using a global feature extraction and edge feature guide mode to obtain high-resolution mask features; and S3, based on the high-resolution mask feature result, focusing the high-resolution mask features by using a decision-level feature fusion method, and outputting a prediction result of the model. According to the invention, the camouflage object can be predicted comprehensively and accurately. 本发明提供一种基于决策级特征融合建模的伪装物体语义分割方法，