AllenNeuralDynamics / AllenNeuralDynamics/aind_data_outreach

compile training-relevant exaspim datasets

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#334 0 則留言 0 個 reaction 已指派 1 人 已被 @tmchartrand 認領 在 GitHub 檢視
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Python
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描述

To better coordinate work on training models for reconstruction correction predictions, we want to create combined data assets and/or DocDB queries that point to all available samples with complete reconstructions from the v2 scope (and possibly also the v1 scope separately). This will likely involve some updates to the metadata, and will need support from Peter and maybe Anna.

not strictly for the NMCP but that's the closest milestone.

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研究方向

Start by reviewing the available DocDB queries and metadata for complete reconstructions in the v2 scope, then check whether v1 should be handled separately. Coordinate with Peter and possibly Anna on the required metadata and training assets; done means all in-scope samples are discoverable through combined assets and/or queries.

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評估

技術堆疊
python
領域
data-engineering, databases
Issue 類型
功能
難度
5/5
預估耗時
一週以上
活躍度
活躍
描述清晰度
需要釐清
新手友好度
25/100

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