add model trained on low-resolution data
Browse files- nn_architecture.txt +19 -0
- trained_model.pth +3 -0
- transformation +0 -0
nn_architecture.txt
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FullyCNN(
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(0): Conv2d(2, 128, kernel_size=(5, 5), stride=(1, 1))
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(1): ReLU()
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(2): Conv2d(128, 64, kernel_size=(5, 5), stride=(1, 1))
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(3): ReLU()
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(4): Conv2d(64, 32, kernel_size=(3, 3), stride=(1, 1))
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(5): ReLU()
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(6): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
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(7): ReLU()
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(8): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
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(9): ReLU()
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(10): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
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(11): ReLU()
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(12): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
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(13): ReLU()
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(14): Conv2d(32, 4, kernel_size=(3, 3), stride=(1, 1))
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(final_transformation): SoftPlusTransform(Parameter containing:
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tensor(0.1000, requires_grad=True))
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)
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trained_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3c8f9bda445fc500382294a56e481d1300cfc57a912cb4006b5e31ab81bd957
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size 1077412
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transformation
ADDED
Binary file (916 Bytes). View file
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