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IEEE/ICACT20250100 Slide.09        [Big Slide]	Oral Presentation
	Squeeze-and-Excitation: To recalibrate feature maps and improve the model's emphasis on more crucial channels, the Squeeze-and-Excitation (SE) module adds a channel-wise attention mechanism, as shown in Figure. Squeeze and excitation are their two primary functions. Global Average Pooling compiles spatial data into a channel description during the squeeze phase. Subsequently, the excitation phase generates channel significance weights using two Dense layers: sigmoid activation and ReLU activation to minimize dimensions. These weights are multiplied by the input feature maps to emphasize important channels and suppress less important ones. By emphasizing important

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