Table 2.

Coordinate attention (CA) and its applications and developments.

Model name	Authors and date	Summarize
Coordinate attention (CA)	Hou et al. (2021)	Incorporating coordinate information into the channel attention mechanism enhances both the visual acuity and overall performance of the network, all the while maintaining a low computational burden and minimizing parameter count
Sparse label assignment (SLA)15	Ming et al. (2021)	Applying CA for object localization in aerial imagery
MSF-MIF16	Yang et al. (2022)	Utilizing the CA module to aid CNN in distinguishing objects in hyperspectral images
Attention-augmented grasp detection network (AAGDN)17	Zhou et al. (2023)	Combining CA with feature fusion and pyramid modules yielded promising results in object detection experiments
Efficient multi-scale attention (EMA)18	Ouyang et al. (2023)	Improvements were made to address channel dimension reduction in CA by grouping features at the channel level and aggregating them with cross-scale interaction methods. Results in classification and object detection tasks validate the effectiveness of this approach