YOLOv5 improvements | 2023 attention | EMAttention attention mechanism (with multiple positions that can be added)

1. Introduction to this article

The improved mechanism brought to you by this article is the EMAttention attention mechanism . Its core idea is to reshape some channels into batch dimensions and group the channel dimensions into multiple sub-features to retain the information of each channel and reduce computational overhead. . The EMA module recalibrates channel weights in each parallel branch by encoding global information and captures pixel-level relationships through cross-dimensional interactions. This article first provides you with a rendering (a comparison of the basic version without any modifications and the improved mechanism of this article) , then introduces its main principles, and finally teaches you how to add the attention mechanism .

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