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Annotation Strategies for Computer Vision Training Data | by Roger Brown | Nov, 2022
It is well known that data science teams dedicate significant time and resources to developing and managing training data for AI and machine learning models — and the principal requisite for it is high-quality computer vision datasets. It is common for problems to stem from poor in-house tooling, labeling rework, difficulty locating data, and difficulties in collaborating & iterating on distributed teams’ data.An organization’s development can be hindered by frequent workflow alterations, large datasets, and an ineffective data training workflow. Growing too rapidly, which is common for startups, regardless of their industry, aggravates these issues.An example is the highly-competitive autonomous vehicle industry, where scalable training-data strategies are vital. The computer vision m...
