Row 78107

Row ID: 78107 | Dataset Entry | Axioma AXP Content Repository

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One thing to take into account when using HSV is that the extremes in the hue channel are similar. It wraps around so to speak, as red is both at 0.0 and 1.0. And the hue channel can change rapidly for regions with close to zero saturation. YUV or LAB is another color space to consider using. In any case, switching between color spaces is a relatively simple transformation which the model should be able to learn on its own. So I wouldn't expect much change in performance.

I concur with the other suggestion in this post to apply shape augmentations (elastic deformation for example) and remove the augmentations which change the color. Also try applying a blurring augmentation to blur out the object textures, as there is evidence to suggest that CNNs are texture biased.

FieldValue
text One thing to take into account when using HSV is that the extremes in the hue channel are similar. It wraps around so to speak, as red is both at 0.0 and 1.0. And the hue channel can change rapidly for regions with close to zero saturation. YUV or LAB is another color space to consider using. In any case, switching between color spaces is a relatively simple transformation which the model should be able to learn on its own. So I wouldn't expect much change in performance. I concur with the ot…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-24
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Raw Record

{
  "text": "One thing to take into account when using HSV is that the extremes in the hue channel are similar. It wraps around so to speak, as red is both at 0.0 and 1.0. And the hue channel can change rapidly for regions with close to zero saturation. YUV or LAB is another color space to consider using. \nIn any case, switching between color spaces is a relatively simple transformation which the model should be able to learn on its own. So I wouldn't expect much change in performance. \n\nI concur with the other suggestion in this post to apply shape augmentations (elastic deformation for example) and remove the augmentations which change the color. Also try applying a blurring augmentation to blur out the object textures, as there is evidence to suggest that CNNs are texture biased.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-24",
  "username_encoded": "Z0FBQUFBQm5Lak1qYWRKajhGekFoRjVoQkhiM0N5N01fdGF1X0FxU3NvLTVDcEJYRjdrTjJEa25vOVNjVERhMjZuSlZpb1JzQzFBLTdCNGZVZnhtZmVKRkFwdG5NeEhnYVE9PQ==",
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