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We have a lot of data normalization to do in our migration. It would be very helpful to be able to extend the `ExecutionContext` of the mappings. I think we should make this part of the DataImport API…
senny updated
10 years ago
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Hi, I noticed you apply a normalization with on noisy rendered images with a constant (1 + sigma^2). (https://github.com/pals-ttic/sjc/blob/main/adapt_sd.py#L133).
I am confused with the intuition…
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First, thank you for sharing your work.
In the dataloader, RGB images are normalized to [0,1], but sparse depth image just divide 256 and convert it to meter, not in the range of [0,1]. Why not norma…
mzy97 updated
4 years ago
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There are different forms of publication dates reported in the Medline/Pubmed data. Many are conventional MM/DD/YYYY dates, however there are things like, "Spring 1996". This issue would involve imple…
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We need to consider the strategy for handling node properties on one node from multiple sources.
As of now, in graph building, nodes merged from different sources use a merging function from KGX t…
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Hi, I've been testing world coordinate loader module, and the output images looks like as if they were completely black, I find there are two normalization process(img / 255 twice), one in "transform"…
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I've been going through the Dhall standard and re-implementing everything from scratch ([in Scala](https://github.com/winitzki/scall)). In general I find the [standard documentation](https://github.co…
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Hello @RubD @andrewdchen,
Does Giotto have any option to run normalization across multiple integrated samples (not individually) to minimize background noise and allow reasonable comparisons?
Seu…
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For the moment, I have only been experimenting with the raw signal data and its FFT transform. However, I am sure much can be gained by cleanup the input signal.
From the top of my head, things worth…
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### Relational Database
- It is a type of database that store and organizes the data in a structured way.
- Data in a relational database is stored in various data tables, each of which has a uniq…