A Fractal Block is an image model block that utilizes an expansion rule that yields a structural layout of truncated fractals. For the base case where $f_{1}\left(z\right) = \text{conv}\left(z\right)$ is a convolutional layer, we then have recursive fractals of the form:
$$ f_{C+1}\left(z\right) = \left[\left(f_{C}\circ{f_{C}}\right)\left(z\right)\right] \oplus \left[\text{conv}\left(z\right)\right]$$
Where $C$ is the number of columns. For the join layer (green in Figure), we use the element-wise mean rather than concatenation or addition.
Source: FractalNet: Ultra-Deep Neural Networks without ResidualsPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Object Recognition | 1 | 33.33% |
Translation | 1 | 33.33% |
Image Classification | 1 | 33.33% |