What is the primary purpose of transfer learning in the context of deep learning for computer vision?
- Training a model from scratch
- Fine-tuning a pre-trained model
- Reducing the number of layers in a neural network
- Converting images into text
Transfer learning in computer vision involves fine-tuning a pre-trained model to adapt it for a new task. It leverages knowledge from a source task to improve performance on a target task, making it more efficient and effective than training from scratch.
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