AI engineering glossary · Computer vision
What is padding?
Padding (also called Zero padding): Extra values, usually zeros, added around the border of an image or feature map before convolution. It lets the kernel be centred on edge pixels and controls output size; 'same' padding keeps the size unchanged while 'valid' uses none.
Padding: an example
A 3 x 3 kernel with padding 1 and stride 1 maps a 32 x 32 input to a 32 x 32 output; with no padding it gives 30 x 30.
Related terms
More Computer vision terms
- Panoptic segmentation
- Patch embedding
- Pixel
- Pooling layer
- Precision and recall for detection
- Pretrained backbone
- R-CNN
- Random crop
Where you learn it
Padding is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.