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Convolutional neural network: Difference between revisions
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Convolutional Neural Network | Convolutional Neural Network | ||
Primarily used for image tasks such as computer vision or image generation, | Primarily used for image tasks such as computer vision or image generation, | ||
though they can be used anywhere you have a rectangular grid with spatial relationship among your data. | though they can be used anywhere you have a rectangular grid with spatial relationship among your data. | ||
Typically convolutional layers are using in blocks consisting of the following: | |||
* Conv2D layer. | |||
** Usually stride 2 for encoders, stride 1 for decoders. | |||
** Often includes some type of padding such as zero padding. | |||
* Upscale layer (for decoders only). | |||
* Normalization or pooling layer (e.g. BatchNorm or MaxPooling). | |||
* Activation (typically ReLU or some variant). | |||
The last layer is typically just a Conv2D with a possible Sigmoid. | |||
==Motivation== | ==Motivation== | ||