1. Introduction to this article
The improved mechanism brought by this article is MLCA (Mixed local channel attention) , which is translated as mixed local channel attention . It combines local and global features as well as channel and spatial feature information. According to the content of the article, it is a lightweight The attention mechanism can greatly improve the detection accuracy by adding a small amount of parameters (as described in the paper). According to my experimental content, the attention mechanism does have very few parameters , and the effect is considered Not bad, and the official code provides secondary innovative ideas and video explanations, which are highly recommended for everyone to watch. At the same time, before I start explaining, I would like to recommend my column . The content of this column supports (classification, detection, segmentation, tracking, key point detection). The column is currently a limited-time discount. Everyone is welcome to subscribe to this column. This column is updated 3-5 times a week. The latest mechanism of this article, as well as files and communication groups containing all my improvements are provided to everyone.
