Beijing Jiaotong University

Ci Liang

Rui Wang

Wei Zheng

Yumei Zhang

A semantic segmentation network model uncertainty quantification method based on evidence inference. The method comprises the steps of constructing an FCN network model, and training the FCN network model by using a training data set to obtain a trained FCN network model for semantic segmentation of image data; transplanting a D-S theory of evidence to the trained FCN network model to obtain a reconstructed FCN network model; and inputting to-be-segmented image data into the reconstructed FCN network model, outputting a classification result of a to-be-segmented image by the FCN network model, and calculating a classification result uncertainty value of each pixel point by using the D-S theory of evidence index.

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Gothenburg, Sweden

Ci Liang