#convolutional-neural-networks

#convolutional-neural-networks

This approach involves decomposing each convolutional layer F into two standard convolutional layers: a filter atom layer D and an atom coefficient layer α with 1 × 1 filters that represent combination rules of filter atoms.

Convolution-based few-shot learning models are still popular for classification tasks in all three domains, adapting quickly to new classes with few examples.