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UID:aug-20-cold-pool-to-hot-queue-annotation-curation-with-fifty-stockholm-20260820@eveny
DTSTAMP:20260728T085300
DTSTART;TZID=Europe/Stockholm:20260820T180000
DTEND;TZID=Europe/Stockholm:20260820T200000
SUMMARY:Aug 20 - Cold Pool to Hot Queue: Annotation Curation with FiftyOne
DESCRIPTION:In this hands-on workshop\, you'll use [FiftyOne ](https://docs.voxel51.com/)to run the full rare-class mining loop end-to-end on a large unlabeled image pool: compress the pool with near-duplicate de…\n\nIn this hands-on workshop\, you'll use [FiftyOne ](https://docs.voxel51.com/)to run the full rare-class mining loop end-to-end on a large unlabeled image pool: compress the pool with near-duplicate detection\, embed images with a modern vision backbone\, mine candidate positives via seeded similarity from a tiny labeled set\, confirm them through targeted human review\, and prioritize the survivors for annotation using representativeness and uniqueness scores.\n\n**Time\, Date and Location**\n\nAug 20\, 2026\n9:00 AM - 11:00 AM PST\, 2026\nOnline. **[Register for the Zoom!](https://voxel51.com/events/from-cold-pool-to-hot-queue-annotation-curation-with-fiftyone-august-20-2026)**\n\n**What You'll Walk Away With**\n\n* A working FiftyOne pipeline for finding rare classes in any visual dataset you own\n* A repeatable four-stage funnel — compress\, mine\, confirm\, prioritize — with a clear objective at each stage\n* A fine-tuned detector that demonstrably outperforms one trained on the same number of randomly sampled images\n* The mental model that data curation — not architecture or hyperparameters — is the highest-leverage thing you can do to improve a rare-class detector\n\nMer info: https://www.meetup.com/stockholm-ai-machine-learning-and-computer-vision-meetup/events/314739450/
LOCATION:Online event\, Stockholm
URL:https://www.meetup.com/stockholm-ai-machine-learning-and-computer-vision-meetup/events/314739450/
SOURCE:https://eveny.nu/event/aug-20-cold-pool-to-hot-queue-annotation-curation-with-fifty-stockholm-20260820
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