What are the main challenges in AI segmentation?

What are the main challenges in AI segmentation?

Some key challenges in AI segmentation include data quality, model complexity, and computational resources.

How does data quality affect segmentation?

Data quality impacts segmentation accuracy; poor data can lead to misclassifications and unreliable results.

What can be done to improve data quality?

Improving data quality can involve data cleaning, augmentation, and ensuring diverse and representative datasets.

Are there specific algorithms that work better for segmentation?

Yes, algorithms like U-Net, Mask R-CNN, and DeepLab are popular for segmentation tasks due to their effectiveness.

What role does computational power play in segmentation?

Computational power is crucial for training complex models efficiently and handling large datasets in segmentation tasks.