Channel Attention

Channel attention aims to strengthen representations in CNNs by learning which feature channels are more important. In tasks where certain filters become especially valuable, this selectivity can improve performance. It is particularly useful in object recognition and fine-grained visual discrimination. It is a specialized form of attention applied not over space, but over the channel dimension.