DensNet169, a well-recognized deep network trained on ImageNet, serves as the foundation for the CBAM-DenseNet- Attention. The selection of DenseNet was based on its effective incorporation of intricate patterns via linked layers, thereby enabling the recycling of features. The DenseNet stages in ...
The DenseNet architecture presents a Convolutional Block Attention Module (CBAM) and Spatial Attention (SA) for the prediction and classification of LSD. Results demonstrate that a 99.11% accuracy can be obtained on the augmented dataset while a 94.23% accuracy can be achieved with the original ...
Last, DenseNet-CBAM network structure combining attention mechanism is proposed for multiple classification task. Experimental results showed that the proposed method achieved the detection accuracy of more than 97% in three different types of mechanical structures with multiple-threaded fasteners, indicating...