What are the main challenges of AI segmentation?

What are the main challenges of AI segmentation?

AI segmentation faces several challenges, including data quality, model complexity, and interpretability.

Can you elaborate on data quality issues?

Sure! Data quality issues can arise from noise, missing values, or imbalanced datasets, affecting model performance.

How does model complexity impact segmentation?

Model complexity can lead to overfitting, where the model learns noise instead of the underlying patterns, reducing generalization.

What about interpretability? Why is it important?

Interpretability is crucial for understanding model decisions, ensuring trust, and facilitating improvements in AI systems.

Are there any solutions to these challenges?

Yes, solutions include improving data preprocessing, using simpler models, and employing techniques for better interpretability.