Development of adaptive activation functions with curvature and range modulation for abstract image feature learning in complex CNNs for cross-domain applications
Deep learning architectures comprise hierarchies in modern machine learning studies, and these are not only full of semantic depth; they are also structured systematically by a sequence of nonlinear transformations. In particular, in convolutional neural networks, the activation functions are the canonical nonlinear co...