Glossary · Phase 4 · Deep learning
Padding
Extra zeros added around an image's edge so a CNN filter can be centered on edge pixels too, and the output shrinks less.
Try it now
The formula from this section, live. Compare the last two lines to see why sharing a small filter is so cheap.
Learn it properly
Convolutional networks · Pattern detectors for images. About 40 minutes.
Other terms from the same lesson
- channel: In images, one layer of numbers per pixel, such as red, green or blue. A CNN layer outputs one channel per filter.
- CNN: A network that slides small pattern-detectors across an image to find edges, shapes and objects.
- feature map: The grid of scores a CNN filter produces: high where its pattern appears in the image, low elsewhere.
- kernel: In a CNN, a small grid of weights that slides over an image and scores how strongly each patch matches a pattern, such as an edge.
- max pooling: Shrinking a feature map by keeping only the biggest value in each small square, so a pattern counts wherever it shows up nearby.
- stride: How many pixels a CNN filter moves at each step. A stride of 2 skips every other spot and halves the output size.
- vision transformer: A transformer for images: it cuts the picture into small patches and treats each patch like a word.
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