What are the main challenges in AI visual analysis?
Some key challenges include data quality, interpretability, and the need for large labeled datasets.
How does data quality affect visual analysis?
Data quality impacts the accuracy of AI models; poor quality data can lead to misleading results.
What is interpretability in the context of AI?
Interpretability refers to how well humans can understand the decisions made by AI models.
Can you give examples of large labeled datasets?
Examples include ImageNet for image classification and COCO for object detection.
What advancements are being made to overcome these challenges?
Advancements include better algorithms, synthetic data generation, and improved annotation tools.
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