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Related Questions
- What is the role of data augmentation in improving the performance of image classification models?
- Can you explain the difference between random cropping, resizing, and padding in image augmentation?
- How does data augmentation impact the training time and computational resources of deep neural networks?
- What are some popular techniques for data augmentation in image classification tasks, such as rotation, flipping, and color jittering?
- Can data augmentation be used to improve the robustness of image classification models to variations in lighting and viewpoint?
- How can data augmentation be used to balance the class distribution in imbalanced datasets?
- Are there any libraries or tools that provide pre-built functions for common data augmentation techniques, such as TensorFlow, PyTorch, or Keras?
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