A novel scaled-gamma-tanh (SGT) activation function in 3D CNN applied for MRI classification.

ABSTRACT: Activation functions in the neural network are responsible for 'firing' the nodes in it. In a deep neural network they 'activate' the features to reduce feature redundancy and learn the complex pattern by adding non-linearity in the network to learn task-specific goals. In this paper, we propose a simple and interesting activation function based on the combination of scaled gamma correction and hyperbolic tangent function, which we call Scaled Gamma Tanh (SGT) activation. The proposed activation function is applied in two steps, first is the calculation of gamma version as y = f(x) = ax^α for x < 0 and y = f(x) = bx^β for x ≥ 0, second is obtaining the squashed value as z = tanh(y). The variables a and b are user-defined constant values whereas [Formula: see text] an

SUBMITTER: Khagi B 

PROVIDER: S-EPMC9440075 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature