On Thu, Jan 5, 2017 at 8:43 PM, Stefan Keller wrote:
>But even if would be 99.8 percent it's important for OSM
> that a human integrates the data into the database.
Just for the record, I agree with this totally. I only see a scenario
where any automatically identified
Hi Philip
On Mon, Dec 19, 2016 at 3:17 PM, Philip Hunt wrote:
> I attended my first Humanitarian OpenStreetMap Team (HOT) mapping event a few
> months ago
> and was interested to see how successful machine learning would be at
> detecting buildings in
> satellite images.
I agree with Rory with the rotated buildings.
However, these building outlines would be great to detect missing buildings
within an area. It's usually very hard to find "missing" buildings when
your HOT Tasking Manager is at 100% completed.
This workflow/tool can definitely be used in the
You've noticed how your algoritm isn't able to get properly rotated
buildings. And this might be an advantage! All buildings being
non-rotated is *obviously* incorrect, so people aren't gonna want to
import them, they'll realise that they have to have a human to
review/correct it.
Perhaps you
Currently my thoughts run along the lines of use it to identify areas with
buildings. Same as Mapswipe?, heavens things get outdated so quickly these
days and Mapswipe hasn't been around for that long.
Secondly if you map them but tag them with something like
possiblebuilding=yes then they
Hi Phillip,
I think Andrew, John, etc. have well covered the practical relevance to
OSM. On a technical note you may consider looking into what the Facebook
data team is doing:
https://code.facebook.com/posts/1676452492623525/connecting-the-world-with-better-maps/
I believe a lot of it is based
I agree with what the others have said so far... this probably won't be
used to feed into the main database but could have other uses.
One place where it could be good is in very sparsely populated areas
like northern Africa, where there are huge areas of empty space with a
few isolated
Hi Philip,
I think this looks really promising. I have seen a fair amount of
machine learning and automated feature extraction results from a
number of different sources, and your examples look as accurate as
anything I have seen.
AI/Machine Learning/Automated Feature Extraction are really
My personal reaction is OpenStreetMap which is the data base behind HOT is
not very open to machine scanning. The reason being they've seen some
fairly poor results in the past.
If you can set up some sort of workflow where the images are manually
verified that might be more acceptable but its
Hi all,
I attended my first Humanitarian OpenStreetMap Team (HOT) mapping event a few
months ago and was interested to see how successful machine learning would be
at detecting buildings in satellite images. The results look promising but I
wanted to know if it could be useful to the community
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