CNNs are good for image recognition and classification. They also excel at natural language processing tasks. An early predecessor called LeNet was built in the late 80s and throughout the 90s. It was mainly used for OCR.
For reference, this article was used.
Glossary and Concepts
- Images are represented by a matrix of values based on their channel
- Channels are the values represented by a component of an image, (e.g. RGB or CMYK). A typical image has 3 components for RGB, a grayscale image has 1 component.
Operations of CNNs
- Convolution
- Non Linearity (ReLU)
- Pooling or sub sampling
- Classification (fully connected sublayer)
Convolution
This is a WIP