基于迁移学习及通道先验注意力机制的地质构造识别

doi:10.16088/j.issn.1001-6600.2024010902

Abstract

Abstract: To address the issue of poor identification resulting from the complex geological background and diverse symbol representations in plane geological drawings, a geological structure recognition model, named MsAttenEfficientNet, is proposed based on transfer learning and the Channel Prior Convolution Attention (CPCA) mechanism. In this model, EfficientNet is utilized as the backbone network architecture, and the Squeeze and Excitation Net (SENet) in the MBConv feature extraction module of EfficientNet are replaced by the CPCA module. This replacement enables the dynamic allocation of channel and spatial attention weights, allowing the model to more accurately capture important regions and spatial structures in the images. Subsequently, improvements are made to the top prediction module by introducing the Swish activation function and Dropout layers to enhance the model’s generalization performance. Finally, the Adam optimization algorithm is employed to improve the convergence speed of the network, and transfer learning is utilized to achieve feature parameter sharing. Experimental results, obtained from training and testing on the geological structure dataset GeoStr18, demonstrate that the MsAttenEfficientNet model achieves a precision of 96.92%, a recall of 96.89%, and an F₁ score of 96.90% in geological structure recognition, outperforming mainstream classification models such as ResNet50, ShuffleNetV2, and DenseNet121, thus effectively applicable for geological structure recognition.

Key words: image recognition, geological structure, EfficientNet network, CPCA, transfer learning

CLC Number: TP183; TP391.41

LIU Junjie, MA Kai, HUANG Zehua, TIAN Miao, QIU Qinjun , TAO Liufeng, XIE Zhong. Geological Structure Recognition Based on Transfer Learning and Channel Prior Attention Mechanism[J].Journal of Guangxi Normal University(Natural Science Edition), 2025, 43(2): 107-120.

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Geological Structure Recognition Based on Transfer Learning and Channel Prior Attention Mechanism

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