Patent ID: 11928792
Assignee: XI'AN JIAOTONG UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. The method of claim 1, wherein a two-stage training strategy is adopted when training a model of the step 2; in a first stage of training, a pixel-wise fusion weight of a feature fusion network is mandatory to be 1, and all parts except the feature fusion module are updated; in a second stage of training, a weight restriction is cancelled, and on a basis of the first stage of training, the entire network is retrained together with the feature fusion module; and in a whole training process, an Adaptive Moment Estimation (ADAM) optimization algorithm is adopted for optimization, and to increase a diversity of training data, a random horizontal flip and a random rotation are adopted to perform data enhancement on the generated plurality of triples of image patches.