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Table 2 The structure of the 3D dense connection DCNN

From: Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method

Layer name Structure
  7×7×7 conv
  3×3×3 max pool
Dense block \(\begin {bmatrix} 1 \times 1 \times 1 \text { conv}\\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×6
Transition 1×1×1 conv2×2×2 avg pool
Dense block \(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×12
Transition 1×1×1 conv2×2×2 avg pool
Dense block \(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×24
Transition 1×1×1 conv2×2×2 avg pool
Dense block \(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×16
  7×7×7 avg pool1000-d FCsoftmax