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Some of the most common applications of machine learning in computer vision include image classification, object detection, and segmentation.
Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.
According to a blog post from Meta, SAM is an image segmentation model that can respond to text prompts or user clicks to isolate specific objects within an image.
Google's newly open-sourced AI image segmentation systems and models are optimized for its cloud TPU hardware, the company says.
Then, it uses that knowledge to create new, artificial image-mask pairs to augment a small dataset of real examples. A segmentation model is trained using both.
Over the past decade, advancements in machine learning (ML) and deep learning (DL) have revolutionized segmentation accuracy.
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