Row 77745

Row ID: 77745 | Dataset Entry | Axioma AXP Content Repository

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Your problem isn't that CNN-based architectures can't learn the colors. It is just that shapes are easier to differentiate with how the convolutions work so they are a much stronger cue, so CNNs use a "shortcut" to make predictions.

There are different debiasing techniques out there, but the first thing I would try would be to use data augmentation by random shape transformations. Then, network will have to learn to differentiate by color.

FieldValue
text Your problem isn't that CNN-based architectures can't learn the colors. It is just that shapes are easier to differentiate with how the convolutions work so they are a much stronger cue, so CNNs use a "shortcut" to make predictions. There are different debiasing techniques out there, but the first thing I would try would be to use data augmentation by random shape transformations. Then, network will have to learn to differentiate by color.
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-24
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Raw Record

{
  "text": "Your problem isn't that CNN-based architectures can't learn the colors. It is just that shapes are easier to differentiate with how the convolutions work so they are a much stronger cue, so CNNs use a \"shortcut\" to make predictions.\n\nThere are different debiasing techniques out there, but the first thing I would try would be to use data augmentation by random shape transformations. Then, network will have to learn to differentiate by color.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-24",
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