Research on salt dome recognition algorithm based on reverse attention mechanism

Li Lou; Fengxia Zhang; Boxun Han

doi:10.1117/12.2655333

7 October 2022 Research on salt dome recognition algorithm based on reverse attention mechanism

Li Lou, Fengxia Zhang, Boxun Han

Proceedings Volume 12344, International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022); 123441I (2022) https://doi.org/10.1117/12.2655333
Event: International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022), 2022, Zhuhai, China

Abstract

In view of the strong subjectivity of traditional salt dome recognition methods and the poor effect of existing deep learning algorithms on salt dome edge recognition, this paper proposes a salt dome recognition algorithm based on reverse attention mechanism, which uses u-net model as the backbone network, adds reverse attention module at the jump connection to extract edge structure information, and finally uses feature splicing to fuse feature information to improve the segmentation performance of network model. Experimental results show that the network achieves good results in salt dome segmentation, and effectively improves the problem of unclear edge segmentation.

Citation Download Citation

Li Lou, Fengxia Zhang, and Boxun Han "Research on salt dome recognition algorithm based on reverse attention mechanism", Proc. SPIE 12344, International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022), 123441I (7 October 2022); https://doi.org/10.1117/12.2655333

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KEYWORDS

Image segmentation

Data modeling

Detection and tracking algorithms

Computer programming

Convolution

Image processing algorithms and systems

Lithium

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