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Chintan2108 / Cloud-Removal-in-Satellite-Images-using-Conditional-Generative-Adversarial-Networks

Removing cloud cover in Sentinel-2 satellite images using only optical data and a novel augmented training approach using conditional GANs.
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Train the model using new data created in issue #4 #5

Open Chintan2108 opened 4 years ago

Chintan2108 commented 4 years ago
Namyalg commented 4 years ago

I would like to work on this

Preetesh21 commented 4 years ago

I would also like to contribute to this issue.

Chintan2108 commented 4 years ago

@Namyalg @Preetesh21 You both can train the model on the new skewed dataset as sampled by @Preetesh21 in issue #4

Namyalg commented 4 years ago

Okay, will do that

Namya LG

On Tue, Oct 27, 2020, 6:21 PM vesper2108 notifications@github.com wrote:

@Namyalg https://github.com/Namyalg @Preetesh21 https://github.com/Preetesh21 You both can train the model on the new skewed dataset as sampled by @Preetesh21 https://github.com/Preetesh21 in issue #4 https://github.com/Chintan2108/Cloud-Removal-in-Satellite-Images-using-Conditional-Generative-Adversarial-Networks/issues/4

  • Train the model using the same hyperparameters
  • Report analytical and comparative model performance
    • Compare your respective models with the current project model (link in readme)
    • Compare each others' model
  • Update readme with a comparison table in terms of our 3 evaluation metrics - PSNR, SSIM and Pearson Correlation
  • Also provide epoch vs error graphs (for both of you)

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