Researchers at USC Propose Self-Attentive Pooling Method for Efficient Deep Learning

In recent years, CNN architectures have made remarkable progress in various challenging vision tasks, including semantic segmentation and object classification. Large activation maps in the initial CNN layers are taking up a lot of on-chip memory due to the continuously rising resolution of pictures acquired by current camera sensors. The pooling operation entails sliding a […]

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