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Related Questions
- What are the key differences between human evaluation and automated metrics for evaluating fairness in image classification models?
- Can you explain the concept of calibration and how it relates to fairness in image classification models?
- How do methods like adversarial training and data augmentation contribute to improving fairness in image classification models?
- What is the role of debiasing techniques in mitigating unfair biases in image classification models?
- Can you provide examples of datasets that have been used to evaluate fairness in image classification models?
- How do ensemble methods, such as bagging and boosting, impact fairness in image classification models?
- What are some common pitfalls to avoid when implementing fairness-aware image classification models in real-world applications?
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