Translations:Convolutional Neural Networks/31/en: Difference between revisions
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Revision as of 21:57, 27 April 2026
- Use pretrained models (transfer learning) when labelled data is limited.
- Prefer small kernels ($ 3 \times 3 $) stacked in depth — two $ 3 \times 3 $ layers have the same receptive field as one $ 5 \times 5 $ layer but with fewer parameters.
- Apply batch normalisation after convolution and before activation.
- Use data augmentation generously to reduce overfitting.
- Replace fully connected layers with global average pooling to reduce parameters.