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Agnieszka Mikołajczyk edited this page Feb 8, 2020
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Welcome to the data-augmentation-review wiki! Data augmentation can be simply described as any method that makes our dataset larger. To create more images for example, we could zoom the in and save a result, we could change the brightness of the image or rotate it. To get bigger sound dataset we could try raise or lower the pitch of the audio sample or slow down/speed up.
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- Affine transformations
- Rotation
- Scaling
- Random cropping
- Reflection
- Elastic transformations
- Contrast shift
- Brightness shift
- Blurring
- Channel shuffle
- Advanced transformations
- Random erasing
- Adding rain effects, sun flare...
- Image blending
- Neural-based transformations
- Adversarial noise
- Neural Style Transfer
- Generative Adversarial Networks
- Affine transformations
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- Noise injection
- Time shift
- Time stretching
- Random cropping
- Pitch scaling
- Dynamic range compression
- Simple gain
- Equalization
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- Thesaurus
- Text Generation
- Back Translation
- Word Embeddings
- Contextualized Word Embeddings