CNN
Convolutional neural network, sharing weights across positions to exploit spatial structure.
Aperçu
A convolutional neural network applies the same small filter at every position of an input, so it learns a pattern once and recognises it anywhere. It solves the parameter explosion that a fully connected layer would suffer on an image, where each pixel would need its own weight. It exists because locality and translation invariance are true of images and largely untrue of language, which is why vision and language ended up with different architectures.
Graphe des technologies
Comment CNN se rattache au reste de la pile.
Utilise et dépend de
- Neural Network concept Algorithms CNN based on Neural Network High ✓ source
Appliqué à
- Image Generation application Applications CNN used for Image Generation Medium ✓ source
Alternatives
Comparaisons
Comparaisons détaillées avec les alternatives ci-dessus.