Labelbox introduces Auto-Segment 2.0 powered by Meta's Segment Anything Model for image segmentation tasks
Auto-Segment 2.0 offers faster and more accurate mask drawing editors for semantic segmentation projects
Application areas include insurance compliance, plant species classification in agriculture, and medical condition diagnosis
SAM data engine and model-assisted labeling capabilities provide enhanced AI development tools
Auto-Segment 2.0 is designed to accelerate AI development and solve segmentation challenges

Labelbox offers a data-centric platform for building AI applications. It includes data labeling, curation, model evaluation, and workflows tailored for AI data set preparation. Users can pre-label data with existing models, compare model predictions with ground truth, and utilize reinforcement learning with human feedback. The platform also features analytics dashboards and tools for evaluating large language models and vision tools. With Labelbox, companies in industries like agriculture, retail, and healthcare can improve their AI models with high-quality training data, optimize model performance, and automate tasks, significantly reducing the time spent on data management and curation.

Labelbox

Platform for data labeling, AI model training, and evaluation.

Introducing Auto-Segment 2.0 for Image Segmentation

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