Convolutional Neural Networks
Convolutional Neural Networks
Local Receptive Fields
- Local receptive fields are small windows that move across the input image.
- Each window connects to a neuron in the next layer.
- This allows the network to capture spatial information.
Convolutional Neural Networks
Shared Weights
- Instead of learning a separate set of weights for each neuron, CNNs learn a single set of weights that are shared across all neurons within a layer.
- All neurons in a layer detect the same feature, but at different locations in the input image.
- To look for multiple features at once, we add layers to our layers!
Convolutional Neural Networks
Pooling
- Pooling is a technique used to reduce the spatial dimensions of the input.
- For example, max pooling takes the maximum value from a small window and passes it to the next layer.
- Think of this like downsizing an image!
Convolutional Neural Networks
Convolutional Neural Networks
Exercise
https://shorturl.at/GRzFo