Faster Semantic Segmentation with Machine Learning-Assisted Workflows

Semantic segmentation is a computer vision task that involves labeling every pixel in an image with a corresponding class. The process of creating this labeled data can be accelerated using machine learning-assisted workflows. These workflows leverage ML models to pre-label images, which human annotators can then review and correct. This approach significantly speeds up the data annotation process and helps break through the data bottleneck common in developing high-quality computer vision models.