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CGIAR Root Volume Estimation Challenge

Helping Africa
$15 000 USD
Completed (over 1 year ago)
Computer Vision
Prediction
1070 joined
257 active
Starti
24 Jan 25
Closei
09 Mar 25
Reveali
10 Mar 25
Whats your cv vs Lb.
Help · 27 Feb 2025, 19:33 · 4

i am using pretrained EfficientNet-B0 as the image encoder and 5 fold cross validation

OOF RMSE: 1.50928179892321

LB 0.978123577

Also any ideas for potential improvment

Discussion 4 answers
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My best efficientnet b0 is 0.98270215 LB 1.4221 4-fold CV

Upvotes 1
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Forget the other chat, but agree with a comment re the number of samples in test (it's not much!). So there will be a big difference here and probably a big shake up in the end. Seems like a gamble to me haha

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EfficientNet-B0 is lightweight. Good baseline, but not optimal.

Trees Hate You Try:

  • EfficientNet-B4 or B5
  • ConvNeXt
  • Swin Transformer

Even a single upgrade here can outperform heavy tuning on B0.

Upvotes 0
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I like the description of CV and LB, it is critical for understanding data interpretation in root volume estimate. It would also be fascinating to investigate how these findings could influence agricultural methods across Africa, particularly in resource-constrained areas. Perhaps combining local knowledge or traditional farming methods with technological breakthroughs could improve accuracy and block blast community engagement.

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