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Integrate active learning from one of the previous projects or implement from scratch.
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This is for tracking interest in Active Learning, which is automatically annotating on new labels based on labels that have been done so far. Please :+1: if this is something you'd like.
From an im…
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We currently support selection of active learning samples via 3 metrics: `confidence`, `margin`, and `negative_entropy`. To this we wish to add a fourth, `batchbald`.
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@thandi1908 @zcapjdb please read before tomorrow
Suppose we train on dataset S1, then we enrich it with more data S2, S1 and S2 come from the same distribution. The training performance will of co…
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**Describe the bug**
At the Active Learning step, whilst being able to view the performance of the classifier with ~60 iterations, upon refreshing the page an error is encountered. Additionally, no i…
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Hi guys,
Are you planning on implementing support for Active Learning or Online Learning for fast object detection labeling in the near future? Cheers, Sam
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Hey Jerin I was going through some lectures and tutorials based on active learning. I have prepared a small ppt based on my understanding of active learning and how we should adapt it for our purpose.…
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Create a new web component and expose a few parameters which control re-learning:
- Number of epochs
- Percentage of data to use for re-training.
When only a subset of data is selected, focus o…
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It would be cool to be able to iteratively update model with new examples, make a prediction and then annotate the most ambiguous ones (like in Prodigy)
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# Reference
- [ ] [ViewAL](https://github.com/nihalsid/ViewAL)
- [ ] [paper - 2019 - ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation](https://arxiv.org/pdf/1911.11789.pdf)
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