convolutional layer & leaky relu (30, 128, 128, 128) (SoftMax Inc)
90
Structured Review
SoftMax Inc
convolutional layer & leaky relu (30, 128, 128, 128)
Convolutional Layer & Leaky Relu (30, 128, 128, 128), supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/convolutional+layer/convolutional+layer+++leaky+relu++30++128++128++128+/us12165330-188-439-455
Average 90 stars, based on 1 article reviews
Convolutional Layer & Leaky Relu (30, 128, 128, 128), supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/convolutional+layer/convolutional+layer+++leaky+relu++30++128++128++128+/us12165330-188-439-455
Average 90 stars, based on 1 article reviews
convolutional layer & leaky relu (30, 128, 128, 128) - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: Article Snippet: As shown in FIGS. 3A-3B, the encoder structure (to the left of the bottleneck convolutional layer) includes: Feature channels, 3D Layer name feature map dimension Input patch image (4, 128, 128, 128) 3 × 3 × 3 Convolutional layer & Leaky ReLU (30, 128, 128, 128) 3 × 3 × 3 Convolutional layer & Leaky ReLU (30, 128, 128, 128) 2 × 2 × 2 Maxpool layer (4, 64, 64, 64) 3 × 3 × 3 Convolutional layer & Leaky ReLU (60, 64, 64, 64) 3 × 3 × 3 Convolutional layer & Leaky ReLU (60, 64, 64, 64) 2 × 2 × 2 Maxpool layer (4, 32, 32, 32) 3 × 3 × 3 Convolutional layer & Leaky ReLU (120, 32, 32, 32) 3 × 3 × 3 Convolutional layer & Leaky ReLU (120, 32, 32, 32) 2 × 2 × 2 Maxpool layer (4, 16, 16, 16) 3 × 3 × 3 Convolutional layer & Leaky ReLU (240, 16, 16, 16) 3 × 3 × 3 Convolutional layer & Leaky ReLU (30, 16, 16, 16) 2 × 2 × 2 Maxpool layer (4, 8, 8, 8) The bottleneck convolutional layer (latent space) includes: Feature channels, 3D Layer name feature map dimension 3 × 3 × 3 Convolutional layer & Leaky ReLU (480, 8, 8, 8) 3 × 3 × 3 Convolutional layer & Leaky ReLU (480, 8, 8, 8) The decoder structure (to the right of the bottleneck convolutional layer) includes: Feature channels, 3D Layer name feature map dimension 2 × 2 × 2 Trilinear up-sampling layer (240, 16, 16, 16) Concatenation of skip connection layers (240, 16, 16, 16) 3 × 3 × 3 Convolutional layer & Leaky ReLU (240, 16, 16, 16) 3 × 3 × 3 Convolutional layer & Leaky ReLU (240, 16, 16, 16) 2 × 2 × 2 Trilinear up-sampling layer (120, 32, 32, 32) Concatenation of skip connection layers (120, 32, 32, 32) 3 × 3 × 3 Convolutional layer & Leaky ReLU (120, 32, 32, 32) 3 × 3 × 3 Convolutional layer & Leaky ReLU (120, 32, 32, 32) 2 × 2 × 2 Trilinear up-sampling layer (30, 64, 64, 64) Concatenation of skip connection layers (30, 64, 64, 64) 3 × 3 × 3 Convolutional layer & Leaky ReLU (60, 64, 64, 64) 3 × 3 × 3 Convolutional layer & Leaky ReLU (60, 64, 64, 64) 2 × 2 × 2 Trilinear up-sampling layer (30, 128, 128, 128) Concatenation of skip connection layers (30, 128, 128, 128) 3 × 3 × 3 Convolutional layer & Leaky ReLU (30, 128, 128, 128) 3 × 3 × 3 Convolutional layer & Leaky ReLU (30, 128, 128, 128) 1 × 1 × 1 Convolutional |