Dam Crack Image Detection Model on Feature Enhancement and Attention Mechanism
نویسندگان
چکیده
Dam crack detection can effectively avoid safety accidents of dams. To solve the problem that dam image samples are not available and traditional algorithm detects cracks with low accuracy, we provide a model based on feature enhancement attention mechanism. Firstly, expand dataset through generative adversarial network (Cracks Enhancements GAN, CE-GAN). It fully data improve quality training data. Secondly, propose mechanism (Attention-based Faster-RCNN, AF-RCNN). The is added in module to give different weights proposal boxes around target fuse candidate high accurately detect location. experimental results show our achieves 81.07% mAP expanded dataset, which 8.39% higher than original Faster-RCNN algorithm. accuracy significantly improved compared other models.
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ژورنال
عنوان ژورنال: Water
سال: 2022
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15010064