Lower-scale inputs can be concatenated to the output of convolutional layers, reinforcing multi-scale features.
This method enhances during training by aligning feature vectors to their class median within a training batch. With/In
(e.g., matching images "with" other images)? Natural Language Processing (e.g., "in-context" learning)? Lower-scale inputs can be concatenated to the output
Here are the key "deep feature" approaches for integration ("With/In"): 1. With/In