Primary competition visual

GeoAI Amazon Basin Secret Runway Detection Challenge by ITU

Helping Austria, Peru
and 1 other country
  • Austria
  • Peru
  • Italy
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2 000 CHF
Challenge completed ~1 year ago
Classification
Earth Observation
394 joined
26 active
Starti
Aug 09, 24
Closei
Nov 11, 24
Reveali
Nov 11, 24
Some people might have gotten high ranks by submitting a large amount of rows. How will you select submissions to score fully?
Platform · 11 Nov 2024, 23:49 · 4

Hi Organizers,

First, thank you for hosting a very interesting competition! I have learned a lot about many different topics, such as acquiring satellite data and understanding EPSG codes for projections.

@meganomaly mentioned at the beginning of the competition that selected submissions from the top 10 would be scored. Since this competition is based on accuracy as a metric, I experimented by submitting submissions containing only zeros and ones. I observed that the metric treats all non-submitted rows as incorrect. This implies that, for example, the top scorer with a score of 0.979390829 must have submitted at least 97.9% of all the rows. However, it was stated that we should only submit a few rows at this stage. I submitted about a million rows, but this makes it impossible to achieve such a high score under the current guidelines.

I used an attention-based segmentation model and did a lot preprocessing of data retrieved from the coordinates of the runways. According to my evals, my model has good performance, but I am unable to achieve a higher score due to the aforementioned issue.

Given this situation, how will you ensure that you run the full scoring on the correct submissions?

Thanks for reading and your assistance!

Best regards, Emil

Discussion 4 answers
User avatar
MICADEE
LAHASCOM

@emilschmitz Nope... I didn't even use up to 200,000 samples. I actually used just 189k plus. However the detection was not that accurate.

12 Nov 2024, 13:57
Upvotes 0

Ah, I'm a bit confused as well. This was my conclusion after submitting 200k of zeros and of ones, which by the definition of accuracy should give the max amount of points reachable with 200k rows. It was quite low (around 0.03).

Neither did I. I used localization and attention-based segmentation. Localization model helped to detect where there could possibly be a runway and simplified the segmentation step. This helped with reducing the size of my submission file.

Wow, you got a really impressive score! Will you publish the model, or are you willing to share it? Would love to see it.