Adaptive adversarial learning-based urban traffic scene semantic segmentation method and system
A technology of semantic segmentation and urban transportation, applied in neural learning methods, image analysis, image data processing, etc., can solve the problems of affecting segmentation accuracy, low segmentation accuracy, complex scenes, etc., to achieve the effect of enhancing generalization ability
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[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.
[0056] The purpose of the present invention is to provide a method and system for semantic segmentation of urban traffic scenes with adaptive confrontation learning, to improve the accuracy of semantic segmentation of complex urban traffic scenes lacking label information and multi-scale targets, and to enhance the generalization ability of semantic segmentation models.
[0057] In order to make the above objectives, features and advantages...
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