CGIAR Crop Damage Classification Challenge
Helping Africa
$10 000 USD
Completed (~2 years ago)
Classification
1148 joined
347 active
Start
Oct 27, 23
Close
Jan 28, 24
Reveal
Jan 28, 24
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Dirty Data?
Platform · 10 Jan 2024, 08:34 · 5
The third Image is definitely mislabelled right?
The dataset has many Images like that(In my opinion were mislabelled),even in Data colunm introduction
were you using all the data or did you clean some images? The best I am getting with using all the data is in 0.6xx range , Thanks in advance.
I used all the data for training, tta and Split data into 5 folds may help you, or a model with larger scale.
And is this consistent in the test set too @Zindi? Because if the test set is clean of these mislabelled images then we have to clean the data , but if also the test set has this mislabelled images what are we supposed to do then? Account for them in our training? @nobody2 @flamethrower @sinchinov @Mohamed_Salam_Jedidi thoughts?
Good question. In the training it looks straight forward to just remove the milabelled/dissimilar images. On Test am skeptical.