Mixed text detection and classification method based on attention mechanism and YOLOv7
Lianqiang Niu, Fenglin Lv · 2023
To improve the accuracy of mixed text classification, CBAM attention mechanism is introduced in the backbone network of YOLOv7 to highlight the key features of dominant category determination. At the same time, aiming at the information loss of PANet route aggregation network, the ASFF adaptive feature fusion mechanism is embedded after it, and the feature map is adaptively weighted by pixels to better preserve the details of the feature map. Experiments show that the Macro-F1 value is improved by 1.9% compared with PSENet + SVM method which detects and classifies first.