What are the applications of domain adaptation in AI?

What are the applications of domain adaptation in AI?

Domain adaptation is used to improve model performance in different but related domains. Common applications include image recognition, natural language processing, and speech recognition.

Can you give me an example of domain adaptation in image recognition?

Sure! For instance, a model trained on images of cats and dogs from one dataset can be adapted to recognize pets in a different dataset with different lighting or backgrounds.

How does domain adaptation improve model accuracy?

It helps the model generalize better by transferring knowledge from a source domain to a target domain, reducing overfitting.

What techniques are commonly used for domain adaptation?

Common techniques include fine-tuning, adversarial training, and feature alignment to bridge the gap between domains.