If you want your machines to see things as they are, you have to supply your data science teams with accurate data that improves your models.
If you expect machines to take actions or make recommendations based on what they see, there's no room for error.
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Semantic Segmentation (Polygons and Masks)
Object Detection
(Bounding Boxes)
Keypoint Labeling
Multi-Page Document Annotation
Inventory Tracking
Visual Question
Answering
Image Captioning
Image Classification
Visual Genome
Optical Character
Recognition (OCR)
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