Object-level remote sensing change detection method and system based on dual related attention
A technology of change detection and attention, applied in neural learning methods, instruments, biological neural network models, etc., can solve the problems of lack of semantic integrity and inability to truly simulate geographic entity targets, and achieve rapid convergence and avoid false positives. The effect of change interference and fast convergence
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[0035] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.
[0036] At the data level, the framework designs a data augmentation method dedicated to change detection, which can effectively speed up the training speed of the model and improve the performance of the model. At the model level, the framework constructs a dual-related attention-guided change detection network, which can effectively extract the overall features and contextual associations of changing objects. The framework finally represents the detected changing geographic entities (such as newly added buildings, artificial structures, etc.) in the form of bounding boxes.
[0037] The embodiment of the present invention provides an object-level remote sensing change detection method based on dual correlation attention, including a data enhancement process dedicated to change detection (such as figure 1 shown) and a dual-rela...
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