Fractal Block

2000년 도입 · 논문 6편에서 사용

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.

출처: FractalNet: Ultra-Deep Neural Networks without Residuals

소개 논문: FractalNet: Ultra-Deep Neural Networks without Residuals