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Computational Analysis and Deep Learning for Medical Care


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smaller than VGG.

Layer name Input size Filter size Window size # Filters Stride/Padding Output size # Feature maps # Parameters
Conv 1 224 × 224 3 × 3 - 64 1/1 224 × 224 64 1,792
Conv 2 224 × 224 3 × 3 - 64 1/1 224 × 224 64 36,928
Max-pooling 1 224 × 224 - 2 × 2 - 2/0 112 × 112 64 0
Conv 3 112 × 112 3 × 3 - 128 1/1 112 × 112 128 73,856
Conv 4 112 × 112 3 × 3 - 128 1/1 112 × 112 128 147,584
Max-pooling 2 112 × 112 - 2 × 2 - 2/0 56 × 56 128 0
Conv 5 56 × 56 3 × 3 - 256 1/1 56 × 56 256 295,168
Conv 6 56 × 56 3 × 3 - 256 1/1 56 × 56 256 590,080
Conv 7 56 × 56 3 × 3 - 256 1/1 56 × 56 256 590,080
Max-pooling 3 56 × 56 - 2 × 2 - 2/0 28 × 28 256 0
Conv 8 28 × 28 3 × 3 - 512 1/1 28 × 28 512 1,180,160
Conv 9 28 × 28 3 × 3 - 512 1/1 28 × 28 512 2,359,808
Conv 10 28 × 28 3 × 3 - 512 1/1 28 × 28 512 2,359,808
28 × 28 - 2 × 2 - 2/0 14 × 14 512 0
Conv 11 14 × 14 3 × 3 - 512 1/1 14 × 14 512 2,359,808
Conv 12 14 × 14 3 × 3 - 512 1/1 14 × 14 512 2,359,808
Conv 13 14 × 14 3 × 3 - 512 1/1 14 × 14 512 2,359,808
Max-pooling 5 14 × 14 - 2 × 2 - 2/0 7 × 7 512 0
Fully connected 1 4,096 neurons